Satellite-derived vertical profiles of temperature and dew point for mesoscale weather forecast

NASA Astrophysics Data System (ADS)

Masselink, Thomas; Schluessel, P.

1995-12-01

Weather forecast-models need spatially high resolutioned vertical profiles of temperature and dewpoint for their initialisation. These profiles can be supplied by a combination of data from the Tiros-N Operational Vertical Sounder (TOVS) and the imaging Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting sate!- lites. In cloudy cases the profiles derived from TOVS data only are of insufficient accuracy. The stanthrd deviations from radiosonde ascents or numerical weather analyses likely exceed 2 K in temperature and 5Kin dewpoint profiles. It will be shown that additional cloud information as retrieved from AVHIRR allows a significant improvement in theaccuracy of vertical profiles. The International TOVS Processing Package (ITPP) is coupled to an algorithm package called AVHRR Processing scheme Over cLouds, Land and Ocean (APOLLO) where parameters like cloud fraction and cloud-top temperature are determined with higher accuracy than obtained from TOVS retrieval alone. Furthermore, a split-window technique is applied to the cloud-free AVHRR imagery in order to derive more accurate surface temperatures than can be obtained from the pure TOVS retrieval. First results of the impact of AVHRR cloud detection on the quality of the profiles are presented. The temperature and humidity profiles of different retrieval approaches are validated against analyses of the European Centre for Medium-Range Weatherforecasts.

Effects of Stratospheric Lapse Rate on Thunderstorm Cloud-Top Structure in a Three-Dimensional Numerical Simulation. Part I: Some Basic Results of Comparative Experiments.

NASA Astrophysics Data System (ADS)

Schlesinger, Robert E.

1988-05-01

An anelastic three-dimensional model is used to investigate the effects of stratospheric temperature lapse rate on cloud top height/temperature structure for strongly sheared mature isolated midlatitude thunderstorms. Three comparative experiments are performed, differing only with respect to the stratospheric stability. The assumed stratospheric lapse rate is 0 K km1 (isothermal) in the first experiment, 3 K km1 in the second, and 3 K km1 (inversion) in the third.Kinematic storm structure is very similar in all three cases, especially in the troposphere. A strong quasi-steady updraft evolves splitting into a dominant cyclonic overshooting right-mover and a weaker anticyclonic left-mover that does not reach the tropopause. Strongest downdrafts occur at low to middle levels between the updrafts, and in the lower stratosphere a few kilometers upshear and downshear of the tapering updraft summit.Each storm shows a cloud-top thermal couplet, relatively cold near and upshear of the summit, and with a `close-in' warm region downshear. Both cold and warm regions become warmer, with significant morphological changes and a lowering of the cloud summit, as stratospheric stability is increased, though the temperature spread is not greatly affected.The coldest and highest cloud-top points are nearly colocated in the absence of a stratospheric inversion, but the coldest point is offset well upshear of the summit when an inversion is present. The cold region as a whole in each case shows at least a transient `V' shape, with the arms pointing downshear, although this shape is persistent only with the inversion.In the experiment with a 3 K km1 stratospheric lapse rate (weakest stability), the warm region is small and separates into two spots with secondary cold spots downshear of them. The warm region becomes larger, and remains single, as stratospheric stability increase. In each run, the warm regions are not accompanied by corresponding cloud-top height minima except very briefly.The cold cloud-top points are near or slightly downwind of relative vertical velocity maxima, usually positive, while the warm points are imbedded in subsidence downwind of the principal cloud-top downdraft core. The storm-relative cloud-top horizontal wind fields are consistent with the `V' shape of the cold region, showing strong diffluent flow directed downshear along the flanks from an upshear stagnation zone.

A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL

NASA Technical Reports Server (NTRS)

Pfister, Leonhard; Ueyama, Rei; Jensen, Eric; Schoeberl, Mark

2017-01-01

Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.

Application of Micro-cloud point extraction for spectrophotometric determination of Malachite green, Crystal violet and Rhodamine B in aqueous samples

NASA Astrophysics Data System (ADS)

Ghasemi, Elham; Kaykhaii, Massoud

2016-07-01

A novel, green, simple and fast method was developed for spectrophotometric determination of Malachite green, Crystal violet, and Rhodamine B in water samples based on Micro-cloud Point extraction (MCPE) at room temperature. This is the first report on the application of MCPE on dyes. In this method, to reach the cloud point at room temperature, the MCPE procedure was carried out in brine using Triton X-114 as a non-ionic surfactant. The factors influencing the extraction efficiency were investigated and optimized. Under the optimized condition, calibration curves were found to be linear in the concentration range of 0.06-0.60 mg/L, 0.10-0.80 mg/L, and 0.03-0.30 mg/L with the enrichment factors of 29.26, 85.47 and 28.36, respectively for Malachite green, Crystal violet, and Rhodamine B. Limit of detections were between 2.2 and 5.1 μg/L.

Application of Micro-cloud point extraction for spectrophotometric determination of Malachite green, Crystal violet and Rhodamine B in aqueous samples.

PubMed

Ghasemi, Elham; Kaykhaii, Massoud

2016-07-05

A novel, green, simple and fast method was developed for spectrophotometric determination of Malachite green, Crystal violet, and Rhodamine B in water samples based on Micro-cloud Point extraction (MCPE) at room temperature. This is the first report on the application of MCPE on dyes. In this method, to reach the cloud point at room temperature, the MCPE procedure was carried out in brine using Triton X-114 as a non-ionic surfactant. The factors influencing the extraction efficiency were investigated and optimized. Under the optimized condition, calibration curves were found to be linear in the concentration range of 0.06-0.60mg/L, 0.10-0.80mg/L, and 0.03-0.30mg/L with the enrichment factors of 29.26, 85.47 and 28.36, respectively for Malachite green, Crystal violet, and Rhodamine B. Limit of detections were between 2.2 and 5.1μg/L. Copyright © 2016 Elsevier B.V. All rights reserved.

In Situ Observations of Thermoreversible Gelation and Phase Separation of Agarose and Methylcellulose Solutions under High Pressure.

PubMed

Kometani, Noritsugu; Tanabe, Masahiro; Su, Lei; Yang, Kun; Nishinari, Katsuyoshi

2015-06-04

Thermoreversible sol-gel transitions of agarose and methylcellulose (MC) aqueous solutions on isobaric cooling or heating under high pressure up to 400 MPa have been investigated by in situ observations of optical transmittance and falling-ball experiments. For agarose, which undergoes the gelation on cooling, the application of pressure caused a gradual rise in the cloud-point temperature over the whole pressure range examined, which is almost consistent with the pressure dependence of gelling temperature estimated by falling-ball experiments, suggesting that agarose gel is stabilized by compression and that the gelation occurs nearly in parallel with phase separation under ambient and high-pressure conditions. For MC, which undergoes the gelation on heating, the cloud-point temperature showed a slight rise with an initial elevation of pressure up to ∼150 MPa, whereas it showed a marked depression above 200 MPa. In contrast, the gelling temperature of MC, which is nearly identical to the cloud-point temperature at ambient pressure, showed a monotonous rise with increasing pressure up to 350 MPa, which means that MC undergoes phase separation prior to gelation on heating under high pressure above 200 MPa. Similar results were obtained for the melting process of MC gel on cooling. The unique behavior of the sol-gel transition of MC under high pressure has been interpreted in terms of the destruction of hydrophobic hydration by compression.

Observation of Sea Ice Surface Thermal States Under Cloud Cover

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Perovich, D. K.; Gow, A. J.; Kwok, R.; Barber, D. G.; Comiso, J. C.; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

Clouds interfere with the distribution of short-wave and long-wave radiations over sea ice, and thereby strongly affect the surface energy balance in polar regions. To evaluate the overall effects of clouds on climatic feedback processes in the atmosphere-ice-ocean system, the challenge is to observe sea ice surface thermal states under both clear sky and cloudy conditions. From laboratory experiments, we show that C-band radar (transparent to clouds) backscatter is very sensitive to the surface temperature of first-year sea ice. The effect of sea ice surface temperature on the magnitude of backscatter change depends on the thermal regimes of sea ice thermodynamic states. For the temperature range above the mirabilite (Na2SO4.10H20) crystallization point (-8.2 C), C-band data show sea ice backscatter changes by 8-10 dB for incident angles from 20 to 35 deg at both horizontal and vertical polarizations. For temperatures below the mirabilite point but above the crystallization point of MgCl2.8H2O (-18.0 C), relatively strong backwater changes between 4-6 dB are observed. These backscatter changes correspond to approximately 8 C change in temperature for both cases. The backscattering mechanism is related to the temperature which determines the thermodynamic distribution of brine volume in the sea ice surface layer. The backscatter is positively correlated to temperature and the process is reversible with thermodynamic variations such as diurnal insolation effects. From two different dates in May 1993 with clear and overcast conditions determined by the Advanced Very High Resolution Radiometer (AVHRR), concurrent Earth Resources Satellite 1 (ERS-1) C-band ice observed with increases in backscatter over first-year sea ice, and verified by increases in in-situ sea ice surface temperatures measured at the Collaborative-Interdisciplinary Cryosphere Experiment (C-ICE) site.

End-group-functionalized poly(N,N-diethylacrylamide) via free-radical chain transfer polymerization: Influence of sulfur oxidation and cyclodextrin on self-organization and cloud points in water

PubMed Central

Reinelt, Sebastian; Steinke, Daniel

2014-01-01

Summary In this work we report the synthesis of thermo-, oxidation- and cyclodextrin- (CD) responsive end-group-functionalized polymers, based on N,N-diethylacrylamide (DEAAm). In a classical free-radical chain transfer polymerization, using thiol-functionalized 4-alkylphenols, namely 3-(4-(1,1-dimethylethan-1-yl)phenoxy)propane-1-thiol and 3-(4-(2,4,4-trimethylpentan-2-yl)phenoxy)propane-1-thiol, poly(N,N-diethylacrylamide) (PDEAAm) with well-defined hydrophobic end-groups is obtained. These end-group-functionalized polymers show different cloud point values, depending on the degree of polymerization and the presence of randomly methylated β-cyclodextrin (RAMEB-CD). Additionally, the influence of the oxidation of the incorporated thioether linkages on the cloud point is investigated. The resulting hydrophilic sulfoxides show higher cloud point values for the lower critical solution temperature (LCST). A high degree of functionalization is supported by 1H NMR-, SEC-, FTIR- and MALDI–TOF measurements. PMID:24778720

Evaluation of Rock Surface Characterization by Means of Temperature Distribution

NASA Astrophysics Data System (ADS)

Seker, D. Z.; Incekara, A. H.; Acar, A.; Kaya, S.; Bayram, B.; Sivri, N.

2017-12-01

Rocks have many different types which are formed over many years. Close range photogrammetry is a techniques widely used and preferred rather than other conventional methods. In this method, the photographs overlapping each other are the basic data source of the point cloud data which is the main data source for 3D model that provides analysts automation possibility. Due to irregular and complex structures of rocks, representation of their surfaces with a large number points is more effective. Color differences caused by weathering on the rock surfaces or naturally occurring make it possible to produce enough number of point clouds from the photographs. Objects such as small trees, shrubs and weeds on and around the surface also contribute to this. These differences and properties are important for efficient operation of pixel matching algorithms to generate adequate point cloud from photographs. In this study, possibilities of using temperature distribution for interpretation of roughness of rock surface which is one of the parameters representing the surface, was investigated. For the study, a small rock which is in size of 3 m x 1 m, located at ITU Ayazaga Campus was selected as study object. Two different methods were used. The first one is production of producing choropleth map by interpolation using temperature values of control points marked on object which were also used in 3D model. 3D object model was created with the help of terrestrial photographs and 12 control points marked on the object and coordinated. Temperature value of control points were measured by using infrared thermometer and used as basic data source in order to create choropleth map with interpolation. Temperature values range from 32 to 37.2 degrees. In the second method, 3D object model was produced by means of terrestrial thermal photographs. Fort this purpose, several terrestrial photographs were taken by thermal camera and 3D object model showing temperature distribution was created. The temperature distributions in both applications are almost identical in position. The areas on the rock surface that roughness values are higher than the surroundings can be clearly identified. When the temperature distributions produced by both methods are evaluated, it is observed that as the roughness on the surface increases, the temperature increases.

Launching a Tethered Balloon in the Artic

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

None

2017-08-14

Sandia atmospheric scientist Dari Dexheimer regularly flies tethered balloons out of Sandia’s dedicated Arctic airspace on Oliktok Point, the northernmost point of Alaska’s Prudhoe Bay. These 13-foot-tall balloons carry distributed temperature sensors to collect Arctic atmospheric temperature profiles, or the temperature of the air at different heights above the ground, among other atmospheric sensors. The data Sandia collects is critical for understanding Arctic clouds to inform global climate models.

Large Scale Ice Water Path and 3-D Ice Water Content

DOE Data Explorer

Liu, Guosheng

2008-01-15

Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.

The potential of cloud point system as a novel two-phase partitioning system for biotransformation.

PubMed

Wang, Zhilong

2007-05-01

Although the extractive biotransformation in two-phase partitioning systems have been studied extensively, such as the water-organic solvent two-phase system, the aqueous two-phase system, the reverse micelle system, and the room temperature ionic liquid, etc., this has not yet resulted in a widespread industrial application. Based on the discussion of the main obstacles, an exploitation of a cloud point system, which has already been applied in a separation field known as a cloud point extraction, as a novel two-phase partitioning system for biotransformation, is reviewed by analysis of some topical examples. At the end of the review, the process control and downstream processing in the application of the novel two-phase partitioning system for biotransformation are also briefly discussed.

Carbon Dioxide Clouds at High Altitude in the Tropics and in an Early Dense Martian Atmosphere

NASA Technical Reports Server (NTRS)

Colaprete, Anthony; Toon, Owen B.

2001-01-01

We use a time dependent, microphysical cloud model to study the formation of carbon dioxide clouds in the Martian atmosphere. Laboratory studies by Glandor et al. show that high critical supersaturations are required for cloud particle nucleation and that surface kinetic growth is not limited. These conditions, which are similar to those for cirrus clouds on Earth, lead to the formation of carbon dioxide ice particles with radii greater than 500 micrometers and concentrations of less than 0.1 cm(exp -3) for typical atmospheric conditions. Within the current Martian atmosphere, CO2 cloud formation is possible at the poles during winter and at high altitudes in the tropics during periods of increased atmospheric dust loading. In both cases, temperature perturbations of several degrees below the CO2 saturation temperature are required to nucleate new cloud particles suggesting that dynamical processes are the most common initiators of carbon dioxide clouds rather than diabatic cooling. The microphysical cloud model, coupled to a two-stream radiative transfer model, is used to reexamine the impact of CO2 clouds on the surface temperature within a dense CO2 atmosphere. The formation of carbon dioxide clouds leads to a warmer surface than what would be expected for clear sky conditions. The amount of warming is sensitive to the presence of dust and water vapor in the atmosphere, both of which act to dampen cloud effects. The radiative warming associated with cloud formation, as well as latent heating, work to dissipate the clouds when present. Thus, clouds never last for periods much longer than several days, limiting their overall effectiveness for warming the surface. The time average cloud optical depth is approximately unity leading to a 5-10 K warming, depending on the surface pressure. However, the surface temperature does not rise about the freezing point of liquid water even for pressures as high as 5 bars, at a solar luminosity of 75% the current value.

Cloud and boundary layer structure over San Nicolas Island during FIRE

NASA Technical Reports Server (NTRS)

Albrecht, Bruce A.; Fairall, Christopher W.; Syrett, William J.; Schubert, Wayne H.; Snider, Jack B.

1990-01-01

The temporal evolution of the structure of the marine boundary layer and of the associated low-level clouds observed in the vicinity of the San Nicolas Island (SNI) is defined from data collected during the First ISCCP Regional Experiment (FIRE) Marine Stratocumulus Intense Field Observations (IFO) (July 1 to 19). Surface, radiosonde, and remote-sensing measurements are used for this analysis. Sounding from the Island and from the ship Point Sur, which was located approximately 100 km northwest of SNI, are used to define variations in the thermodynamic structure of the lower-troposphere on time scales of 12 hours and longer. Time-height sections of potential temperature and equivalent potential temperature clearly define large-scale variations in the height and the strength of the inversion and periods where the conditions for cloud-top entrainment instability (CTEI) are met. Well defined variations in the height and the strength of the inversion were associated with a Cataline Eddy that was present at various times during the experiment and with the passage of the remnants of a tropical cyclone on July 18. The large-scale variations in the mean thermodynamic structure at SNI correlate well with those observed from the Point Sur. Cloud characteristics are defined for 19 days of the experiment using data from a microwave radiometer, a cloud ceilometer, a sodar, and longwave and shortwave radiometers. The depth of the cloud layer is estimated by defining inversion heights from the sodar reflectivity and cloud-base heights from a laser ceilometer. The integrated liquid water obtained from NOAA's microwave radiometer is compared with the adiabatic liquid water content that is calculated by lifting a parcel adiabatically from cloud base. In addition, the cloud structure is characterized by the variability in cloud-base height and in the integrated liquid water.

An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model

NASA Technical Reports Server (NTRS)

Peterson, Thomas C.; Barnett, Tim P.; Roeckner, Erich; Vonder Haar, Thomas H.

1992-01-01

The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.

Lidar observations of Arctic polar stratospheric clouds, 1988 - Signature of small, solid particles above the frost point

NASA Technical Reports Server (NTRS)

Poole, L. R.; Osborn, M. T.; Hunt, W. H.

1988-01-01

The paper presents recent (January 1988) Arctic airborne lidar data which suggest that Type I polar stratospheric clouds (PSCs) are composed of small solid particles with radii on the order of 0.5 micron. PSCs were observed remotely in the 21-24 km altitude range north of Greenland during a round-trip flight from Andenes, Norway on January 29, 1988, aboard the NASA Wallops Flight Facility P-3 Orion aircraft. Synoptic analyses at the 30-mb level show local temperatures of 191-193 K, which are well above the estimated frost point temperature of 185 K; this suggests that the PSCs were probably of the binary HNO3-H2O (Type I) class.

Cirrus cloud model parameterizations: Incorporating realistic ice particle generation

NASA Technical Reports Server (NTRS)

Sassen, Kenneth; Dodd, G. C.; Starr, David OC.

1990-01-01

Recent cirrus cloud modeling studies have involved the application of a time-dependent, two dimensional Eulerian model, with generalized cloud microphysical parameterizations drawn from experimental findings. For computing the ice versus vapor phase changes, the ice mass content is linked to the maintenance of a relative humidity with respect to ice (RHI) of 105 percent; ice growth occurs both with regard to the introduction of new particles and the growth of existing particles. In a simplified cloud model designed to investigate the basic role of various physical processes in the growth and maintenance of cirrus clouds, these parametric relations are justifiable. In comparison, the one dimensional cloud microphysical model recently applied to evaluating the nucleation and growth of ice crystals in cirrus clouds explicitly treated populations of haze and cloud droplets, and ice crystals. Although these two modeling approaches are clearly incompatible, the goal of the present numerical study is to develop a parametric treatment of new ice particle generation, on the basis of detailed microphysical model findings, for incorporation into improved cirrus growth models. For example, the relation between temperature and the relative humidity required to generate ice crystals from ammonium sulfate haze droplets, whose probability of freezing through the homogeneous nucleation mode are a combined function of time and droplet molality, volume, and temperature. As an example of this approach, the results of cloud microphysical simulations are presented showing the rather narrow domain in the temperature/humidity field where new ice crystals can be generated. The microphysical simulations point out the need for detailed CCN studies at cirrus altitudes and haze droplet measurements within cirrus clouds, but also suggest that a relatively simple treatment of ice particle generation, which includes cloud chemistry, can be incorporated into cirrus cloud growth.

Cloud point extraction thermospray flame quartz furnace atomic absorption spectrometry for determination of ultratrace cadmium in water and urine

NASA Astrophysics Data System (ADS)

Wu, Peng; Zhang, Yunchang; Lv, Yi; Hou, Xiandeng

2006-12-01

A simple, low cost and highly sensitive method based on cloud point extraction (CPE) for separation/preconcentration and thermospray flame quartz furnace atomic absorption spectrometry was proposed for the determination of ultratrace cadmium in water and urine samples. The analytical procedure involved the formation of analyte-entrapped surfactant micelles by mixing the analyte solution with an ammonium pyrrolidinedithiocarbamate (APDC) solution and a Triton X-114 solution. When the temperature of the system was higher than the cloud point of Triton X-114, the complex of cadmium-PDC entered the surfactant-rich phase and thus separation of the analyte from the matrix was achieved. Under optimal chemical and instrumental conditions, the limit of detection was 0.04 μg/L for cadmium with a sample volume of 10 mL. The analytical results of cadmium in water and urine samples agreed well with those by ICP-MS.

Laboratory measurements of heterogeneous CO2 ice nucleation on nanoparticles under conditions relevant to the Martian mesosphere

NASA Astrophysics Data System (ADS)

Nachbar, Mario; Duft, Denis; Mangan, Thomas Peter; Martin, Juan Carlos Gomez; Plane, John M. C.; Leisner, Thomas

2016-05-01

Clouds of CO2 ice particles have been observed in the Martian mesosphere. These clouds are believed to be formed through heterogeneous nucleation of CO2 on nanometer-sized meteoric smoke particles (MSPs) or upward propagated Martian dust particles (MDPs). Large uncertainties still exist in parameterizing the microphysical formation process of these clouds as key physicochemical parameters are not well known. We present measurements on the nucleation and growth of CO2 ice on sub-4 nm radius iron oxide and silica particles representing MSPs at conditions close to the mesosphere of Mars. For both particle materials we determine the desorption energy of CO2 to be ΔFdes = (18.5 ± 0.2) kJ mol-1 corresponding to ΔFdes = (0.192 ± 0.002) eV and obtain m = 0.78 ± 0.02 for the contact parameter that governs heterogeneous nucleation by analyzing the measurements using classical heterogeneous nucleation theory. We did not find any temperature dependence for the contact parameter in the temperature range examined (64 K to 73 K). By applying these values for MSPs in the Martian mesosphere, we derive characteristic temperatures for the onset of CO2 ice nucleation, which are 8-18 K below the CO2 frost point temperature, depending on particle size. This is in line with the occurrence of highly supersaturated conditions extending to 20 K below frost point temperature without the observation of clouds. Moreover, the sticking coefficient of CO2 on solid CO2 was determined to be near unity. We further argue that the same parameters can be applied to CO2 nucleation on upward propagated MDPs.

Spectrophotometric determination of paracetamol in urine with tetrahydroxycalix[4]arene as a coupling reagent and preconcentration with triton X-114 using cloud point extraction.

PubMed

Filik, Hayati; Sener, Izzet; Cekiç, Sema Demirci; Kiliç, Emine; Apak, Reşat

2006-06-01

In the present paper, conventional spectrophotometry in conjunction with cloud point extraction-preconcentration were investigated as alternative methods for paracetamol (PCT) assay in urine samples. Cloud point extraction (CPE) was employed for the preconcentration of p-aminophenol (PAP) prior to spectrophotometric determination using the non-ionic surfactant Triton X-114 (TX-114) as an extractant. The developed methods were based on acidic hydrolysis of PCT to PAP, which reacted at room temperature with 25,26,27,28-tetrahydroxycalix[4]arene (CAL4) in the presence of an oxidant (KIO(4)) to form an blue colored product. The PAP-CAL4 blue dye formed was subsequently entrapped in the surfactant micelles of Triton X-114. Cloud point phase separation with the aid of Triton X-114 induced by addition of Na(2)SO(4) solution was performed at room temperature as an advantage over other CPE assays requiring elevated temperatures. The 580 nm-absorbance maximum of the formed product was shifted bathochromically to 590 nm with CPE. The working range of 1.5-12 microg ml(-1) achieved by conventional spectrophotometry was reduced down to 0.14-1.5 microg ml(-1) with cloud point extraction, which was lower than those of most literature flow-through assays that also suffer from nonspecific absorption in the UV region. By preconcentrating 10 ml sample solution, a detection limit as low as 40.0 ng ml(-1) was obtained after a single-step extraction, achieving a preconcentration factor of 10. The stoichiometric composition of the dye was found to be 1 : 4 (PAP : CAL4). The impact of a number of parameters such as concentrations of CAL4, KIO(4), Triton X-100 (TX-100), and TX-114, extraction temperature, time periods for incubation and centrifugation, and sample volume were investigated in detail. The determination of PAP in the presence of paracetamol in micellar systems under these conditions is limited. The established procedures were successfully adopted for the determination of PCT in urine samples. Since the drug is rapidly absorbed and excreted largely in urine and its high doses have been associated with lethal hepatic necrosis and renal failure, development of a rapid, sensitive and selective assay of PCT is of vital importance for fast urinary screening and antidote administration before applying more sophisticated, but costly and laborious hyphenated instrumental techniques of HPLC-SPE-NMR-MS.

Validation of Local-Cloud Model Outputs With the GOES Satellite Imagery

NASA Astrophysics Data System (ADS)

Malek, E.

2005-05-01

Clouds (visible aggregations of minute droplets of water or tiny crystals of ice suspended in the air) affect the radiation budget of our planet by reflecting, absorbing and scattering solar radiation, and the re-emission of terrestrial radiation. They affect the weather and climate by positive or negative feedbacks. Many researchers have worked on the parameterization of clouds and their effects on the radiation budget. There is little information about ground-based approaches for continuous evaluation of cloud, such as cloud base height, cloud base temperature, and cloud coverage, at local and regional scales. This present article deals with the development of an algorithm for continuous (day and night) evaluation of cloud base temperature, cloud base height and percent of skies covered by cloud at local scale throughout the year. The Vaisala model CT-12K laser beam ceilometer is used at the Automated Surface Observing Systems (ASOS) to measure the cloud base height and report the sky conditions on an hourly basis or at shorter intervals. This laser ceilometer is a fixed-type whose transmitter and receiver point straight up at the cloud (if any) base. It is unable to measure clouds that are not above the sensor. To report cloudiness at the local scale, many of these type of ceilometers are needed. This is not a perfect method for cloud measurement. A single cloud hanging overhead the sensor will cause overcast readings, whereas, a hole in the clouds could cause a clear reading to be reported. To overcome this problem, we have set up a ventilated radiation station at Logan-Cache airport, Utah, U.S.A., since 1995, which is equipped with one of the above-mentioned ceilometers. This radiation station (composed of pyranometers, pyrgeometers and net radiometer) provides continuous measurements of incoming and outgoing shortwave and longwave radiation and the net radiation throughout the year. We have also measured the surface temperature and pressure, the 2-m air temperature and humidity, precipitation, and the 3-m wind and direction at this station. Having the air temperature, moisture, and the measured cloudless incoming longwave (atmospheric) radiation during 1999 through 2004, based upon the ASOS and the algorithm data, we found the appropriate formula (among four reported approaches) for computation of the cloudless-skies atmospheric emissivity. Considering the additional longwave radiation captured by the facing-up pyrgeometer during the cloudy skies, coming from the cloud in the wave band which the gaseous emission lacks (from 8-13 ìm), we developed an algorithm which provides the continuous 20-min cloud information (cloud base height, cloud base temperature, and percent of skies covered by cloud) over the Cache Valley during day and night throughout the year. The comparisons between the ASOS and the algorithm data during the period of 8-12 June, 2004 are reported in this article. The proposed algorithm is a promising approach for evaluation of the cloud base temperature, cloud base height, and percent of skies covered by cloud at the local scale throughout the year. It also reports the comparison between model outputs and GOES 10 satellite images.

Synthesis and physical properties of new estolide esters

USDA-ARS?s Scientific Manuscript database

Vegetable oil-based oils usually fail to meet the rigorous demands of industrial lubricants by not having acceptable low temperature properties, pour point (PP) and/or cloud point (CP). The oleic estolide was esterified with a series of 16 different alcohols that were either branched or straight-cha...

Synthesis and physical properties of new coco-oleic estolide branched esters

USDA-ARS?s Scientific Manuscript database

Oils derived from vegetable oils tend to not meet the standards for industrial lubricants because of unacceptable low temperature properties, pour point (PP), and/or cloud point (CP). However, a catalytic amount of perchloric acid with oleic and coconut (coco) fatty acids produced a coco-oleic estol...

Cloud-top structure of tornadic storms on 10 April 1979 from rapid scan and stereo satellite observations

NASA Technical Reports Server (NTRS)

Negri, A. J.

1982-01-01

Stereoscopic data from near-synchronous eastern and western GOES satellite 3 min interval visible and IR measurements and ground-based radar are used to examine the Wichita Falls, TX tornado of April, 1979. The visible wavelength scan was at 0.6 micron, while the IR was at 11 microns, and additional IR blackbody temperatures were acquired from the Tiros-N spacecraft. A minimum cloud top temperature of 208 K located the point of tornadogenesis. The cloud top cooling rate was determined to be 7 K/21 min above the tropopause preceding the tornado, while a warm area at 221 K developed downwind at the same time. It was found that temperature differences of 10 K can exist between GOES and Tiros-N anvil top measurements, and reach 20 K in the case of a young thunderstorm.

Pyrophoric sulfides influence over the minimum ignition temperature of dust cloud

NASA Astrophysics Data System (ADS)

Prodan, Maria; Lupu, Leonard Andrei; Ghicioi, Emilian; Nalboc, Irina; Szollosi-Mota, Andrei

2017-12-01

The dust cloud is the main form of existence of combustible dust in the production area and together with the existence of effective ignition sources are the main causes of dust explosions in production processes. The minimum ignition temperature has an important role in the process of selecting the explosion-protected electrical equipment when performing the explosion risk assessment of combustible dusts. The heated surfaces are able to ignite the dust clouds that can form in process industry. The oil products usually contain hydrogen sulfide and thus on the pipe walls iron sulfides can form, which can be very dangerous from health and safety point of view. In order to study the influence of the pyrophoric sulfide over the minimum ignition temperature of combustible dusts for this work were performed several experiments on a residue collected from the oil pipes contaminated with commercially iron sulfide.

Nonionic Cellulose Ethers as Potential Drug Delivery Systems for Periodontal Anesthesia.

PubMed

Scherlund; Brodin; Malmsten

2000-09-15

Nonionic cellulose ethers displaying a lower consolute temperature, or cloud-point, close to body temperature were investigated as potential carrier systems for the delivery of local anesthetic agents to the periodontal pocket. The interaction between the polymers, i.e., ethyl(hydroxyethyl)cellulose (EHEC) and hydrophobically modified EHEC (HM-EHEC), and ionic surfactants was determined in the absence and in the presence of the local anesthetic agents lidocaine and prilocaine. The cloud-point and rheology data indicate interactions between the polymer and both anionic and cationic surfactants. More precisely, a number of ionic surfactants were found to result in an increase in cloud-point at higher surfactant concentrations, a surfactant-concentration-dependent thickening, and a temperature-induced gelation upon heating. Upon addition of the local anesthetic agents lidocaine and prilocaine in their uncharged form to EHEC and HM-EHEC, in the absence of surfactants, only minor interaction with the polymer could be inferred. However, these substances were found to affect the polymer-surfactant interaction. In particular, the drug release rate in vitro as well as the stability and temperature-dependent viscosity were followed for an EHEC/SDS system and EHEC/myristoylcholine bromide system upon addition of lidocaine and prilocaine. The data indicate a possibility of formulating a local anesthetic drug delivery system suitable for administration into the periodontal pocket where at least small amounts of active ingredients can be incorporated into the system without severely affecting the gelation behavior. The results found for the cationic myristoylcholine bromide system are particularly interesting for the application in focus here since this surfactant is antibacterial and readily biodegradable. Copyright 2000 Academic Press.

A method for quantifying cloud immersion in a tropical mountain forest using time-lapse photography

USGS Publications Warehouse

Bassiouni, Maoya; Scholl, Martha A.; Torres-Sanchez, Angel J.; Murphy, Sheila F.

2017-01-01

Quantifying the frequency, duration, and elevation range of fog or cloud immersion is essential to estimate cloud water deposition in water budgets and to understand the ecohydrology of cloud forests. The goal of this study was to develop a low-cost and high spatial-coverage method to detect occurrence of cloud immersion within a mountain cloud forest by using time-lapse photography. Trail cameras and temperature/relative humidity sensors were deployed at five sites covering the elevation range from the assumed lifting condensation level to the mountain peaks in the Luquillo Mountains of Puerto Rico. Cloud-sensitive image characteristics (contrast, the coefficient of variation and the entropy of pixel luminance, and image colorfulness) were used with a k-means clustering approach to accurately detect cloud-immersed conditions in a time series of images from March 2014 to May 2016. Images provided hydrologically meaningful cloud-immersion information while temperature-relative humidity data were used to refine the image analysis using dew point information and provided temperature gradients along the elevation transect. Validation of the image processing method with human-judgment based classification generally indicated greater than 90% accuracy. Cloud-immersion frequency averaged 80% at sites above 900 m during nighttime hours and 49% during daytime hours, and was consistent with diurnal patterns of cloud immersion measured in a previous study. Results for the 617 m site demonstrated that cloud immersion in the Luquillo Mountains rarely occurs at the previously-reported cloud base elevation of about 600 m (11% during nighttime hours and 5% during daytime hours). The framework presented in this paper will be used to monitor at a low cost and high spatial resolution the long-term variability of cloud-immersion patterns in the Luquillo Mountains, and can be applied to ecohydrology research at other cloud-forest sites or in coastal ecosystems with advective sea fog.

A Herschel-SPIRE Survey of the MonR2 Giant Molecular Cloud

NASA Astrophysics Data System (ADS)

Pokhrel, Riwaj; Gutermuth, Robert A.; Ali, Babar; Megeath, S. Thomas; Pipher, Judith; Myers, Philip C.; Fischer, William J.; Henning, Thomas; Wolk, Scott J.; Allen, Lori; Tobin, John J.

2014-06-01

We present a new survey of the MonR2 giant molecular cloud with SPIRE on the Herschel Space Observatory. We cross-calibrated SPIRE data with Planck-HFI and accounted for its absolute offset and zero point correction. We fixed emissivity with the help of flux-error and flux ratio plots. As the best representation of cold dusty molecular clouds, we did greybody fits of the SEDs. We studied the nature of distribution of column densities above and below certain critical limit, followed by the mass and temperature distributions for different regions. We isolated the filaments and studied radial column density profile in this cloud.

Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities

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

Liu, Guosheng

2013-03-15

Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term ofmore » condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMs cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve ice water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional ice water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud ice water contents in support of cloud modeling activities. The approach of the study is to expand a (surface) point measurement to an (satellite) area measurement. That is, the study takes the advantage of the high quality cloud measurements (particularly cloud radar and microwave radiometer measurements) at the point of the ARM sites. We use the cloud ice water characteristics derived from the point measurement to guide/constrain a satellite retrieval algorithm, then use the satellite algorithm to derive the 3-D cloud ice water distributions within an 10° (latitude) x 10° (longitude) area. During the research period, we have developed, validated and improved our cloud ice water retrievals, and have produced and archived at ARM website as a PI-product of the 3-D cloud ice water contents using combined satellite high-frequency microwave and surface radar observations for SGP March 2000 IOP and TWP-ICE 2006 IOP over 10 deg. x 10 deg. area centered at ARM SGP central facility and Darwin sites. We have also worked on validation of the 3-D ice water product by CloudSat data, synergy with visible/infrared cloud ice water retrievals for better results at low ice water conditions, and created a long-term (several years) of ice water climatology in 10 x 10 deg. area of ARM SGP and TWP sites and then compared it with GCMs.« less

Kinetics of laser irradiated nanoparticles cloud

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Upadhyay Kahaly, M.; Misra, Shikha

2018-02-01

A comprehensive kinetic model describing the complex kinetics of a laser irradiated nanoparticle ensemble has been developed. The absorbed laser radiation here serves dual purpose, viz., photoenhanced thermionic emission via rise in its temperature and direct photoemission of electrons. On the basis of mean charge theory along with the equations for particle (electron) and energy flux balance over the nanoparticles, the transient processes of charge/temperature evolution over its surface and mass diminution on account of the sublimation (phase change) process have been elucidated. Using this formulation phenomenon of nanoparticle charging, its temperature rise to the sublimation point, mass ablation, and cloud disintegration have been investigated; afterwards, typical timescales of disintegration, sublimation and complete evaporation in reference to a graphite nanoparticle cloud (as an illustrative case) have been parametrically investigated. Based on a numerical analysis, an adequate parameter space describing the nanoparticle operation below the sublimation temperature, in terms of laser intensity, wavelength and nanoparticle material work function, has been identified. The cloud disintegration is found to be sensitive to the nanoparticle charging through photoemission; as a consequence, it illustrates that radiation operating below the photoemission threshold causes disintegration in the phase change state, while above the threshold, it occurs with the onset of surface heating.

July 2012 Greenland melt extent enhanced by low-level liquid clouds.

PubMed

Bennartz, R; Shupe, M D; Turner, D D; Walden, V P; Steffen, K; Cox, C J; Kulie, M S; Miller, N B; Pettersen, C

2013-04-04

Melting of the world's major ice sheets can affect human and environmental conditions by contributing to sea-level rise. In July 2012, an historically rare period of extended surface melting was observed across almost the entire Greenland ice sheet, raising questions about the frequency and spatial extent of such events. Here we show that low-level clouds consisting of liquid water droplets ('liquid clouds'), via their radiative effects, played a key part in this melt event by increasing near-surface temperatures. We used a suite of surface-based observations, remote sensing data, and a surface energy-balance model. At the critical surface melt time, the clouds were optically thick enough and low enough to enhance the downwelling infrared flux at the surface. At the same time they were optically thin enough to allow sufficient solar radiation to penetrate through them and raise surface temperatures above the melting point. Outside this narrow range in cloud optical thickness, the radiative contribution to the surface energy budget would have been diminished, and the spatial extent of this melting event would have been smaller. We further show that these thin, low-level liquid clouds occur frequently, both over Greenland and across the Arctic, being present around 30-50 per cent of the time. Our results may help to explain the difficulties that global climate models have in simulating the Arctic surface energy budget, particularly as models tend to under-predict the formation of optically thin liquid clouds at supercooled temperatures--a process potentially necessary to account fully for temperature feedbacks in a warming Arctic climate.

Jovian meterology: Large-scale moist convection without a lower boundary

NASA Technical Reports Server (NTRS)

Gierasch, P. J.

1975-01-01

It is proposed that Jupiter's cloud bands represent large scale convection whose character is determined by the phase change of water at a level where the temperature is about 275K. It is argued that there are three important layers in the atmosphere: a tropopause layer where emission to space occurs; an intermediate layer between the tropopause and the water cloud base; and the deep layer below the water cloud. All arguments are only semi-quantitative. It is pointed out that these ingredients are essential to Jovian meteorology.

Accuracy and precision of polar lower stratospheric temperatures from reanalyses evaluated from A-Train CALIOP and MLS, COSMIC GPS RO, and the equilibrium thermodynamics of supercooled ternary solutions and ice clouds

NASA Astrophysics Data System (ADS)

Lambert, Alyn; Santee, Michelle L.

2018-02-01

We investigate the accuracy and precision of polar lower stratospheric temperatures (100-10 hPa during 2008-2013) reported in several contemporary reanalysis datasets comprising two versions of the Modern-Era Retrospective analysis for Research and Applications (MERRA and MERRA-2), the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-I), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (NCEP-CFSR). We also include the Goddard Earth Observing System model version 5.9.1 near-real-time analysis (GEOS-5.9.1). Comparisons of these datasets are made with respect to retrieved temperatures from the Aura Microwave Limb Sounder (MLS), Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Global Positioning System (GPS) radio occultation (RO) temperatures, and independent absolute temperature references defined by the equilibrium thermodynamics of supercooled ternary solutions (STSs) and ice clouds. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of polar stratospheric clouds are used to determine the cloud particle types within the Aura MLS geometric field of view. The thermodynamic calculations for STS and the ice frost point use the colocated MLS gas-phase measurements of HNO3 and H2O. The estimated bias and precision for the STS temperature reference, over the 68 to 21 hPa pressure range, are 0.6-1.5 and 0.3-0.6 K, respectively; for the ice temperature reference, they are 0.4 and 0.3 K, respectively. These uncertainties are smaller than those estimated for the retrieved MLS temperatures and also comparable to GPS RO uncertainties (bias < 0.2 K, precision > 0.7 K) in the same pressure range. We examine a case study of the time-varying temperature structure associated with layered ice clouds formed by orographic gravity waves forced by flow over the Palmer Peninsula and compare how the wave amplitudes are reproduced by each reanalysis dataset. We find that the spatial and temporal distribution of temperatures below the ice frost point, and hence the potential to form ice polar stratospheric clouds (PSCs) in model studies driven by the reanalyses, varies significantly because of the underlying differences in the representation of mountain wave activity. High-accuracy COSMIC temperatures are used as a common reference to intercompare the reanalysis temperatures. Over the 68-21 hPa pressure range, the biases of the reanalyses with respect to COSMIC temperatures for both polar regions fall within the narrow range of -0.6 K to +0.5 K. GEOS-5.9.1, MERRA, MERRA-2, and JRA-55 have predominantly cold biases, whereas ERA-I has a predominantly warm bias. NCEP-CFSR has a warm bias in the Arctic but becomes substantially colder in the Antarctic. Reanalysis temperatures are also compared with the PSC reference temperatures. Over the 68-21 hPa pressure range, the reanalysis temperature biases are in the range -1.6 to -0.3 K with standard deviations ˜ 0.6 K for the CALIOP STS reference, and in the range -0.9 to +0.1 K with standard deviations ˜ 0.7 K for the CALIOP ice reference. Comparisons of MLS temperatures with the PSC reference temperatures reveal vertical oscillations in the MLS temperatures and a significant low bias in MLS temperatures of up to 3 K.

Revised Correlation between Odin/OSIRIS PMC Properties and Coincident TIMED/SABER Mesospheric Temperatures

NASA Technical Reports Server (NTRS)

Feofilov, A. G.; Petelina, S V.; Kutepov, A. A.; Pesnell, W. D.; Goldberg, R. A.; Llewellyn, E. J.; Russell, J. M.

2006-01-01

The Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on board the Odin satellite detects Polar Mesospheric Clouds (PMCs) through the enhancement in the limb scattered solar radiance. The Sounding of the Atmosphere using the Broadband Emission Radiometry (SABER) instrument on board the TIMED satellite is a limb scanning infrared radiometer that measures temperature and vertical profiles and energetic parameters for minor constituents in the mesosphere and lower thermosphere. The combination of OSIRIS and SABER data has been previously used to statistically derive thermal conditions for PMC existence [Petelina et al., 2005]. In this work, we employ the simultaneous common volume measurements of PMCs by OSIRIS and temperature profiles measured by SABER for the Northern Hemisphere summers of 2002-2005 and corrected in the polar region by accounting for the vibrational-vibrational energy exchange among the CO2 isotopes [Kutepov et al., 2006]. For each of 20 coincidences identified within plus or minus 1 degree latitude, plus or minus 2 degrees longitude and less than 1 hour time the frost point temperatures were calculated using the corresponding SABER temperature profile and water vapor densities of 1,3, and 10 ppmv. We found that the PMC presence and brightness correlated only with the temperature threshold that corresponds to the frost point. The absolute value of the temperature below the frost point, however, didn't play a significant role in the intensity of PMC signal for the majority of selected coincidences. The presence of several bright clouds at temperatures above the frost point is obviously related to the limitation of the limb geometry when some near- or far-field PMCs located at higher (and warmer) altitudes appear to be at lower altitudes.

Revised Correlation between Odin/OSIRIS PMC Properties and Coincident TIMED/SABER Mesospheric Temperatures

NASA Technical Reports Server (NTRS)

Feofilov, A. G.; Petelina, S. V.; Kutepov, A. A.; Pesnell, W. D.; Goldberg, R. A.; Llewellyn, E. J.; Russell, J. M.

2006-01-01

The Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on board the Odin satellite detects Polar Mesospheric Clouds (PMCs) through the enhancement in the limb-scattered solar radiance. The Sounding of the Atmosphere using the Broadband Emission Radiometry (SABER) instrument on board the TIMED satellite is a limb scanning infrared radiometer that measures temperature and vertical profiles and energetic parameters for minor constituents in the mesosphere and lower thermosphere. The combination of OSIRIS and SABER data has been previously used to statistically derive thermal conditions for PMC existence [Petelina et al., 2005]. a, A.A. Kutepov, W.D. Pesnell, In this work, we employ the simultaneous common volume measurements of PMCs by OSIRIS and temperature profiles measured by SABER for the Northern Hemisphere summers of 2002-2005 and corrected in the polar region by accounting for the vibrational-vibrational energy exchange among the CO2 isotopes [Kutepov et al., 2006]. For each of 20 coincidences identified within plus or minus 1 degree latitude, plus or minus 2 degrees longitude and less than 1 hour time the frost point temperatures were calculated using the corresponding SABER temperature profile and water vapor densities of 1,3, and 10 ppmv. We found that the PMC presence and brightness correlated only with the temperature threshold that corresponds to the frost point. The absolute value of the temperature below the frost point, however, didn't play a significant role in the intensity of PMC signal for the majority of selected coincidences. The presence of several bright clouds at temperatures above the frost point is obviously related to the limitation of the limb geometry when some near- or far-field PMCs located at higher (and warmer) altitudes appear to be at lower altitudes.

Observational constraints on mixed-phase clouds imply higher climate sensitivity

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

Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D.

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO 2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here, in this paper, we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. Finally, wemore » point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback.« less

Observational constraints on mixed-phase clouds imply higher climate sensitivity

DOE PAGES

Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D.

2016-04-08

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO 2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here, in this paper, we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. Finally, wemore » point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback.« less

Observational constraints on mixed-phase clouds imply higher climate sensitivity.

PubMed

Tan, Ivy; Storelvmo, Trude; Zelinka, Mark D

2016-04-08

Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. We point out the need for realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback. Copyright © 2016, American Association for the Advancement of Science.

Acoustic-wave sensor apparatus for analyzing a petroleum-based composition and sensing solidification of constituents therein

DOEpatents

Spates, J.J.; Martin, S.J.; Mansure, A.J.

1997-08-26

An acoustic-wave sensor apparatus and method are disclosed. The apparatus for analyzing a normally liquid petroleum-based composition includes at least one acoustic-wave device in contact with the petroleum-based composition for sensing or detecting the presence of constituents (e.g. paraffins or petroleum waxes) therein which solidify upon cooling of the petroleum-based composition below a cloud-point temperature. The acoustic-wave device can be a thickness-shear-mode device (also termed a quartz crystal microbalance), a surface-acoustic-wave device, an acoustic-plate-mode device or a flexural plate-wave device. Embodiments of the present invention can be used for measuring a cloud point, a pour point and/or a freeze point of the petroleum-based composition, and for determining a temperature characteristic of each point. Furthermore, measurements with the acoustic-wave sensor apparatus can be made off-line by using a sample having a particular petroleum-based composition; or in-situ with the petroleum-based composition contained within a pipeline or storage tank. The acoustic-wave sensor apparatus has uses in many different petroleum technology areas, including the recovery, transport, storage, refining and use of petroleum and petroleum-based products. 7 figs.

Acoustic-wave sensor apparatus for analyzing a petroleum-based composition and sensing solidification of constituents therein

DOEpatents

Spates, James J.; Martin, Stephen J.; Mansure, Arthur J.

1997-01-01

An acoustic-wave sensor apparatus and method. The apparatus for analyzing a normally liquid petroleum-based composition includes at least one acoustic-wave device in contact with the petroleum-based composition for sensing or detecting the presence of constituents (e.g. paraffins or petroleum waxes) therein which solidify upon cooling of the petroleum-based composition below a cloud-point temperature. The acoustic-wave device can be a thickness-shear-mode device (also termed a quartz crystal mircrobalance), a surface-acoustic-wave device, an acoustic-plate-mode device or a flexural plate-wave device. Embodiments of the present invention can be used for measuring a cloud point, a pour point and/or a freeze point of the petroleum-based composition, and for determining a temperature characteristic of each point. Furthermore, measurements with the acoustic-wave sensor apparatus can be made off-line by using a sample having a particular petroleum-based composition; or in-situ with the petroleum-based composition contained within a pipeline or storage tank. The acoustic-wave sensor apparatus has uses in many different petroleum technology areas, including the recover transport, storage, refining and use of petroleum and petroleum-based products.

Deep convective clouds at the tropopause

NASA Astrophysics Data System (ADS)

Aumann, H. H.; Desouza-Machado, S. G.

2010-07-01

Data from the Advanced Infrared Sounder (AIRS) on the EOS Aqua spacecraft identify thousands of cloud tops colder than 225 K, loosely referred to as Deep Convective Clouds (DCC). Many of these cloud tops have "inverted" spectra, i.e. areas of strong water vapor, CO2 and ozone opacity, normally seen in absorption, are now seen in emission. We refer to these inverted spectra as DCCi. They are found in about 0.4% of all spectra from the tropical oceans excluding the Western Tropical Pacific (WTP), 1.1% in the WTP. The cold clouds are the anvils capping thunderstorms and consist of optically thick cirrus ice clouds. The precipitation rate associated with DCCi suggests that imbedded in these clouds, protruding above them, and not spatially resolved by the AIRS 15 km FOV, are even colder bubbles, where strong convection pushes clouds to within 5 hPa of the pressure level of the tropopause cold point. Associated with DCCi is a local upward displacement of the tropopause, a cold "bulge", which can be seen directly in the brightness temperatures of AIRS and AMSU channels with weighting function peaking between 40 and 2 hPa, without the need for a formal temperature retrieval. The bulge is not resolved by the analysis in numerical weather prediction models. The locally cold cloud tops relative to the analysis give the appearance (in the sense of an "illusion") of clouds overshooting the tropopause and penetrating into the stratosphere. Based on a simple model of optically thick cirrus clouds, the spectral inversions seen in the AIRS data do not require these clouds to penetrate into the stratosphere. However, the contents of the cold bulge may be left in the lower stratosphere as soon as the strong convection subsides. The heavy precipitation and the distortion of the temperature structure near the tropopause indicate that DCCi are associated with intense storms. Significant long-term trends in the statistical properties of DCCi could be interesting indicators of climate change.

Climatology and Formation of Tropical Midlevel Clouds at the Darwin ARM Site

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

Riihimaki, Laura D.; McFarlane, Sally A.; Comstock, Jennifer M.

A 4-yr climatology of midlevel clouds is presented from vertically pointing cloud lidar and radar measurements at the Atmospheric Radiation Measurement Program (ARM) site at Darwin, Australia. Few studies exist of tropical midlevel clouds using a dataset of this length. Seventy percent of clouds with top heights between 4 and 8 km are less than 2 km thick. These thin layer clouds have a peak in cloud-top temperature around the melting level (0°C) and also a second peak around -12.5°C. The diurnal frequency of thin clouds is highest during the night and reaches a minimum around noon, consistent with variationmore » caused by solar heating. Using a 1.5-yr subset of the observations, the authors found that thin clouds have a high probability of containing supercooled liquid water at low temperatures: ~20% of clouds at -30°C, ~50% of clouds at -20°C, and ~65% of clouds at -10°C contain supercooled liquid water. The authors hypothesize that thin midlevel clouds formed at the melting level are formed differently during active and break monsoon periods and test this over three monsoon seasons. A greater frequency of thin midlevel clouds are likely formed by increased condensation following the latent cooling of melting during active monsoon periods when stratiform precipitation is most frequent. This is supported by the high percentage (65%) of midlevel clouds with preceding stratiform precipitation and the high frequency of stable layers slightly warmer than 0°C. In the break monsoon, a distinct peak in the frequency of stable layers at 0°C matches the peak in thin midlevel cloudiness, consistent with detrainment from convection.« less

Impact of fatty ester composition on low temperature properties of biodiesel-petroleum diesel blends

USDA-ARS?s Scientific Manuscript database

Several biodiesel fuels along with neat fatty acid methyl esters (FAMEs) commonly encountered in biodiesel were blended with ultra-low sulfur diesel (ULSD) fuel at low blend levels permitted by ASTM D975 (B1-B5) and cold flow properties such as cloud point (CP), cold filter plugging point (CFPP), an...

Preliminary Findings of Inflight Icing Field Test to Support Icing Remote Sensing Technology Assessment

NASA Technical Reports Server (NTRS)

King, Michael; Reehorst, Andrew; Serke, Dave

2015-01-01

NASA and the National Center for Atmospheric Research have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage will utilize a vertical pointing cloud radar, a multifrequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport.

Impact of Albedo Contrast Between Cirrus and Boundary-Layer Clouds on Climate Sensitivity

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Lindzen, R. S.; Hou, A. Y.; Lau, William K. M. (Technical Monitor)

2001-01-01

In assessing the iris effect suggested by Lindzen et al. (2001), Fu et al. (2001) found that the response of high-level clouds to the sea surface temperature had an effect of reducing the climate sensitivity to external radiative forcing, but the effect was not as strong as LCH found. This weaker reduction in climate sensitivity was due to the smaller contrasts in albedos and effective emitting temperatures between cirrus clouds and the neighboring regions. FBH specified the albedos and the outgoing longwave radiation (OLR) in the LCH 3.5-box radiative-convective model by requiring that the model radiation budgets at the top of the atmosphere be consistent with that inferred from the Earth Radiation Budget Experiment (ERBE). In point of fact, the constraint by radiation budgets alone is not sufficient for deriving the correct contrast in radiation properties between cirrus clouds and the neighboring regions, and the approach of FBH to specifying those properties is, we feel inappropriate for assessing the iris effect.

Overshooting cloud top, variation of tropopause and severe storm formation

NASA Technical Reports Server (NTRS)

Hung, R. J.; Smith, R. E.

1984-01-01

The development of severe multicell thunderstorms leading to the touchdown of six tornados near Pampa, TX, on May 19-20, 1982, is characterized in detail on the basis of weather maps, rawinsonde data, and radar summaries, and the results are compared with GOES rapid-scan IR images. The multicell storm cloud is shown to have formed beginning at 1945 GMT at the point of highest horizontal moisture convergence and lowest tropopause height and to have penetrated the tropopause at 2130 GMT, reaching a maximum altitude and a cloud-top black-body temperature 9 C lower than the tropopause temperature at 2245 GMT and collapsing about 20 min, when the firt tornado touched down. The value of the real-time vertical profiles provided by satellite images in predicting which severe storms will produce tornados or other violent phenomena is stressed.

Super Clausius-Clapeyron scaling of extreme hourly precipitation and its relation to large-scale atmospheric conditions

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Barbero, Renaud; Loriaux, Jessica; Fowler, Hayley

2017-04-01

Present-day precipitation-temperature scaling relations indicate that hourly precipitation extremes may have a response to warming exceeding the Clausius-Clapeyron (CC) relation; for The Netherlands the dependency on surface dew point temperature follows two times the CC relation corresponding to 14 % per degree. Our hypothesis - as supported by a simple physical argument presented here - is that this 2CC behaviour arises from the physics of convective clouds. So, we think that this response is due to local feedbacks related to the convective activity, while other large scale atmospheric forcing conditions remain similar except for the higher temperature (approximately uniform warming with height) and absolute humidity (corresponding to the assumption of unchanged relative humidity). To test this hypothesis, we analysed the large-scale atmospheric conditions accompanying summertime afternoon precipitation events using surface observations combined with a regional re-analysis for the data in The Netherlands. Events are precipitation measurements clustered in time and space derived from approximately 30 automatic weather stations. The hourly peak intensities of these events again reveal a 2CC scaling with the surface dew point temperature. The temperature excess of moist updrafts initialized at the surface and the maximum cloud depth are clear functions of surface dew point temperature, confirming the key role of surface humidity on convective activity. Almost no differences in relative humidity and the dry temperature lapse rate were found across the dew point temperature range, supporting our theory that 2CC scaling is mainly due to the response of convection to increases in near surface humidity, while other atmospheric conditions remain similar. Additionally, hourly precipitation extremes are on average accompanied by substantial large-scale upward motions and therefore large-scale moisture convergence, which appears to accelerate with surface dew point. This increase in large-scale moisture convergence appears to be consequence of latent heat release due to the convective activity as estimated from the quasi-geostrophic omega equation. Consequently, most hourly extremes occur in precipitation events with considerable spatial extent. Importantly, this event size appears to increase rapidly at the highest dew point temperature range, suggesting potentially strong impacts of climatic warming.

Atmospheric Retrieval Analysis of the Directly Imaged Exoplanet HR 8799b

NASA Astrophysics Data System (ADS)

Lee, Jae-Min; Heng, Kevin; Irwin, Patrick G. J.

2013-12-01

Directly imaged exoplanets are unexplored laboratories for the application of the spectral and temperature retrieval method, where the chemistry and composition of their atmospheres are inferred from inverse modeling of the available data. As a pilot study, we focus on the extrasolar gas giant HR 8799b, for which more than 50 data points are available. We upgrade our non-linear optimal estimation retrieval method to include a phenomenological model of clouds that requires the cloud optical depth and monodisperse particle size to be specified. Previous studies have focused on forward models with assumed values of the exoplanetary properties; there is no consensus on the best-fit values of the radius, mass, surface gravity, and effective temperature of HR 8799b. We show that cloud-free models produce reasonable fits to the data if the atmosphere is of super-solar metallicity and non-solar elemental abundances. Intermediate cloudy models with moderate values of the cloud optical depth and micron-sized particles provide an equally reasonable fit to the data and require a lower mean molecular weight. We report our best-fit values for the radius, mass, surface gravity, and effective temperature of HR 8799b. The mean molecular weight is about 3.8, while the carbon-to-oxygen ratio is about unity due to the prevalence of carbon monoxide. Our study emphasizes the need for robust claims about the nature of an exoplanetary atmosphere to be based on analyses involving both photometry and spectroscopy and inferred from beyond a few photometric data points, such as are typically reported for hot Jupiters.

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, K.; Gettelman, A.; Craig, C.; ...

2015-06-30

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into amore » microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, Katherine; Gettelman, A.; Craig, Cheryl; ...

2015-12-01

Most global climate models parameterize separate cloud types using separate parameterizations.This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysicsmore » scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. In conclusion, the new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, perceptible water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less

Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

NASA Astrophysics Data System (ADS)

Kohira, K.; Masuda, H.

2017-09-01

A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

The registration of non-cooperative moving targets laser point cloud in different view point

NASA Astrophysics Data System (ADS)

Wang, Shuai; Sun, Huayan; Guo, Huichao

2018-01-01

Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser threedimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.

Antarctic Temperature Extremes from MODIS Land Surface Temperatures: New Processing Methods Reveal Data Quality Puzzles

NASA Astrophysics Data System (ADS)

Grant, G.; Gallaher, D. W.

2017-12-01

New methods for processing massive remotely sensed datasets are used to evaluate Antarctic land surface temperature (LST) extremes. Data from the MODIS/Terra sensor (Collection 6) provides a twice-daily look at Antarctic LSTs over a 17 year period, at a higher spatiotemporal resolution than past studies. Using a data condensation process that creates databases of anomalous values, our processes create statistical images of Antarctic LSTs. In general, the results find few significant trends in extremes; however, they do reveal a puzzling picture of inconsistent cloud detection and possible systemic errors, perhaps due to viewing geometry. Cloud discrimination shows a distinct jump in clear-sky detections starting in 2011, and LSTs around the South Pole exhibit a circular cooling pattern, which may also be related to cloud contamination. Possible root causes are discussed. Ongoing investigations seek to determine whether the results are a natural phenomenon or, as seems likely, the results of sensor degradation or processing artefacts. If the unusual LST patterns or cloud detection discontinuities are natural, they point to new, interesting processes on the Antarctic continent. If the data artefacts are artificial, MODIS LST users should be alerted to the potential issues.

The dust cloud of the century

NASA Astrophysics Data System (ADS)

Robock, A.

1983-02-01

The structure and composition of the dust cloud from the 4 April 1982 eruption of the El Chichon volcano in Chiapas state, Mexico, is examined and the possible effects of the dust cloud on the world's weather patterns are discussed. Observations of the cloud using a variety of methods are evaluated, including data from the GOES and NOAA-7 weather satellites, vertically pointing lidar measurements, the SME satellite, and the Nimbus-7 satellite. Studies of the gaseous and particulate composition of the cloud reveal the presence of large amounts of sulfuric acid particles, which have a long mean residence time in the atmosphere and have a large effect on the amount of solar radiation received at the earth's surface by scattering several percent of the radiation back to space. Estimates of the effect of this cloud on surface air temperature changes are presented based on findings from climate models.

Comparative verification between GEM model and official aviation terminal forecasts

NASA Technical Reports Server (NTRS)

Miller, Robert G.

1988-01-01

The Generalized Exponential Markov (GEM) model uses the local standard airways observation (SAO) to predict hour-by-hour the following elements: temperature, pressure, dew point depression, first and second cloud-layer height and amount, ceiling, total cloud amount, visibility, wind, and present weather conditions. GEM is superior to persistence at all projections for all elements in a large independent sample. A minute-by-minute GEM forecasting system utilizing the Automated Weather Observation System (AWOS) is under development.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features.

PubMed

He, Ying; Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-08-11

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features

PubMed Central

Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-01-01

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value. PMID:28800096

Hole punch clouds over the Bahamas

NASA Image and Video Library

2017-12-08

In elementary school, students learn that water freezes at 0 degrees Celsius (32 degrees Fahrenheit). That is true most of the time, but there are exceptions to the rule. For instance, water with very few impurities (such as dust or pollution particles, fungal spores, bacteria) can be chilled to much cooler temperatures and still remain liquid—a process known as supercooling. Supercooling may sound exotic, but it occurs pretty routinely in Earth’s atmosphere. Altocumulus clouds, a common type of mid-altitude cloud, are mostly composed of water droplets supercooled to a temperature of about -15 degrees C. Altocumulus clouds with supercooled tops cover about 8 percent of Earth’s surface at any given time. Supercooled water droplets play a key role in the formation of hole-punch and canal clouds, the distinctive clouds shown in these satellite images. Hole-punch clouds usually appear as circular gaps in decks of altocumulus clouds; canal clouds look similar but the gaps are longer and thinner. This true-color image shows hole-punch and canal clouds off the coast of Florida, as observed on December 12, 2014, by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. Both types of cloud form when aircraft fly through cloud decks rich with supercooled water droplets and produce aerodynamic contrails. Air expands and cools as it moves around the wings and past the propeller, a process known as adiabatic cooling. Air temperatures over jet wings often cool by as much as 20 degrees Celsius, pushing supercooled water droplets to the point of freezing. As ice crystals form, they absorb nearby water droplets. Since ice crystals are relatively heavy, they tend to sink. This triggers tiny bursts of snow or rain that leave gaps in the cloud cover. Whether a cloud formation becomes a hole-punch or canal depends on the thickness of the cloud layer, the air temperature, and the degree of horizontal wind shear. Both descending and ascending aircraft—including jets and propeller planes—can trigger hole-punch and canal clouds. The nearest major airports in the images above include Miami International, Fort Lauderdale International, Grand Bahama International, and Palm Beach International. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team 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

On the hydrophilicity of polyzwitterion poly (N,N-dimethyl-N-(3-(methacrylamido)propyl)ammoniopropane sulfonate) in water, deuterated water, and aqueous salt solutions.

PubMed

Hildebrand, Viet; Laschewsky, André; Zehm, Daniel

2014-01-01

A series of zwitterionic model polymers with defined molar masses up to 150,000 Da and defined end groups are prepared from sulfobetaine monomer N,N-dimethyl-N-(3-(methacrylamido)propyl)ammoniopropanesulfonate (SPP). Polymers are synthesized by reversible addition-fragmentation chain transfer polymerization (RAFT) using a functional chain transfer agent labeled with a fluorescent probe. Their upper critical solution temperature-type coil-to-globule phase transition in water, deuterated water, and various salt solutions is studied by turbidimetry. Cloud points increase with polyzwitterion concentration and molar mass, being considerably higher in D2O than in H2O. Moreover, cloud points are strongly affected by the amount and nature of added salts. Typically, they increase with increasing salt concentration up to a maximum value, whereas further addition of salt lowers the cloud points again, mostly down to below freezing point. The different salting-in and salting-out effects of the studied anions can be correlated with the Hofmeister series. In physiological sodium chloride solution and in phosphate buffered saline (PBS), the cloud point is suppressed even for high molar mass samples. Accordingly, SPP-polymers behave strongly hydrophilic under most conditions encountered in biomedical applications. However, the direct transfer of results from model studies in D2O, using, e.g. (1)H NMR or neutron scattering techniques, to 'normal' systems in H2O is not obvious.

2D modeling of direct laser metal deposition process using a finite particle method

NASA Astrophysics Data System (ADS)

Anedaf, T.; Abbès, B.; Abbès, F.; Li, Y. M.

2018-05-01

Direct laser metal deposition is one of the material additive manufacturing processes used to produce complex metallic parts. A thorough understanding of the underlying physical phenomena is required to obtain a high-quality parts. In this work, a mathematical model is presented to simulate the coaxial laser direct deposition process tacking into account of mass addition, heat transfer, and fluid flow with free surface and melting. The fluid flow in the melt pool together with mass and energy balances are solved using the Computational Fluid Dynamics (CFD) software NOGRID-points, based on the meshless Finite Pointset Method (FPM). The basis of the computations is a point cloud, which represents the continuum fluid domain. Each finite point carries all fluid information (density, velocity, pressure and temperature). The dynamic shape of the molten zone is explicitly described by the point cloud. The proposed model is used to simulate a single layer cladding.

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

A Herschel-SPIRE Survey of the MonR2 Giant Molecular Cloud

NASA Astrophysics Data System (ADS)

Pokhrel, Riwaj; Gutermuth, Robert; Ali, Babar; Megeath, Thomas; Pipher, Judith; Myers, Philip; Fischer, William; Henning, Thomas; Wolk, Scott; Allen, Lori; Tobin, John

2015-08-01

We present a new survey of the MonR2 giant molecular cloud with SPIRE on the Herschel Space Observatory. We cross-calibrated SPIRE data with Planck-HFI and accounted for its absolute offset and zero point correction. We fixed emissivity with the help of flux-error and flux ratio plots. As the best representation of cold dusty molecular clouds, we did greybody fits of the SEDs. We studied the nature of distribution of column densities above and below certain critical limit, followed by the mass and temperature distributions for different regions. We used dendrograms as a technique to study the hierarchical structures in the GMC.

The effects of atmospheric cloud radiative forcing on climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1989-01-01

In order to isolate the effects of atmospheric cloud radiative forcing (ACRF) on climate, the general circulation of an ocean-covered earth called 'Seaworld' was simulated using the Colorado State University GCM. Most current climate models, however, do not include an interactive ocean. The key simplifications in 'Seaworld' are the fixed boundary temperature with no land points, the lack of mountains and the zonal uniformity of the boundary conditions. Two 90-day 'perpetual July' simulations were performed and analyzed the last sixty days of each. The first run included all the model's physical parameterizations, while the second omitted the effects of clouds in both the solar and terrestrial radiation parameterizations. Fixed and identical boundary temperatures were set for the two runs, and resulted in differences revealing the direct and indirect effects of the ACRF on the large-scale circulation and the parameterized hydrologic processes.

Evidence That Nitric Acid Increases Relative Humidity in Low-Temperature Cirrus Clouds

NASA Technical Reports Server (NTRS)

Gao, R. S.; Popp, P. J.; Fahey, D. W.; Marcy, T. P.; Herman, R. L.; Weinstock, E. M.; Baumgardner, D. G.; Garrett, T. J.; Rosenlof, K. H.; Thompson, T. L.

2004-01-01

In situ measurements of the relative humidity with respect to ice (RH(sub(i)) and of nitric acid (HNO3) were made in both natural and contrail cirrus clouds in the upper troposphere. At temperatures lower than 202 kelvin, RH(sub i) values show a sharp increase to average values of over 130% in both cloud types. These enhanced RH(sub i) values are attributed to the presence of a new class of NHO3- containing ice particles (Delta-ice). We propose that surface HNO3 molecules prevent the ice/vapor system from reaching equilibrium by a mechanism similar to that of freezing point depression by antifreeze proteins. Delta-ice represents a new link between global climate and natural and anthropogenic nitrogen oxide emissions. Including Delta-ice in climate models will alter simulated cirrus properties and the distribution of upper tropospheric water vapor.

Development of modulated optical transmission system to determinate the cloud and freezing points in biofuels.

PubMed

Jaramillo-Ochoa, Liliana; Ramirez-Gutierrez, Cristian F; Sánchez-Moguel, Alonso; Acosta-Osorio, Andrés; Rodriguez-Garcia, Mario E

2015-01-01

This work is focused in the development of a modulated optical transmission system with temperature control to determine the thermal properties of biodiesels such as the cloud and freezing points. This system is able to determine these properties in real time without relying on the operator skills as indicated in the American Society for Testing Materials (ASTM) norms. Thanks to the modulation of the incident laser, the noise of the signal is reduced and two information channels are generated: amplitude and phase. Lasers with different wavelengths can be used in this system but the sample under study must have optical absorption at the wavelength of the laser.

Registration algorithm of point clouds based on multiscale normal features

NASA Astrophysics Data System (ADS)

Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

2015-01-01

The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

Observational Evidence Against Mountain-Wave Generation of Ice Nuclei as a Prerequisite for the Formation of Three Solid Nitric Acid Polar Stratospheric Clouds Observed in the Arctic in Early December 1999

NASA Technical Reports Server (NTRS)

Pagan, Kathy L.; Tabazadeh, Azadeh; Drdla, Katja; Hervig, Mark E.; Eckermann, Stephen D.; Browell, Edward V.; Legg, Marion J.; Foschi, Patricia G.

2004-01-01

A number of recently published papers suggest that mountain-wave activity in the stratosphere, producing ice particles when temperatures drop below the ice frost point, may be the primary source of large NAT particles. In this paper we use measurements from the Advanced Very High Resolution Radiometer (AVHRR) instruments on board the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites to map out regions of ice clouds produced by stratospheric mountain-wave activity inside the Arctic vortex. Lidar observations from three DC-8 flights in early December 1999 show the presence of solid nitric acid (Type Ia or NAT) polar stratospheric clouds (PSCs). By using back trajectories and superimposing the position maps on the AVHRR cloud imagery products, we show that these observed NAT clouds could not have originated at locations of high-amplitude mountain-wave activity. We also show that mountain-wave PSC climatology data and Mountain Wave Forecast Model 2.0 (MWFM-2) raw hemispheric ray and grid box averaged hemispheric wave temperature amplitude hindcast data from the same time period are in agreement with the AVHRR data. Our results show that ice cloud formation in mountain waves cannot explain how at least three large scale NAT clouds were formed in the stratosphere in early December 1999.

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

NASA Astrophysics Data System (ADS)

Galewsky, J.

2017-12-01

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

Accuracy assessment of building point clouds automatically generated from iphone images

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2014-06-01

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.

Jovian Dark Spot

NASA Technical Reports Server (NTRS)

1998-01-01

A recently discovered black spot in Jupiter's clouds is darker than any feature ever before observed on the giant planet. The spot may be the result of a downward spiraling wind that blows away high clouds and reveals deeper, very dark cloud layers. These three panels depict the same area of Jupiter's atmosphere. A map of Jovian temperatures near 250 millibar pressure (top) panel is derived from the photopolarimeter-radiometer instrument on NASA's Galileo Jupiter orbiter. This map is compared with maps derived from images of the same area in visible light (middle panel)and thermal radiation sensitive to cloud-top temperatures (bottom panel).

The single downward-pointing arrow in the top panel indicates the location of a warm area that corresponds to the position of a so-called 'black spot'(shown in the middle panel), a feature that is about a year old. Features this dark are rare on Jupiter. The bottom panel, sensitive to temperatures at Jupiter's cloud tops, shows this feature as a bright object, meaning that upper-level cold clouds are missing - allowing us to see deeper into Jupiter's warmer interior. The dark visible appearance of the feature than most likely represents the color of very deep clouds. The warm temperatures and cloud-free conditions imply that this feature is a region where dry upper-atmospheric gas is being forced to converge, is warmed up and then forced to descend, clearing out clouds. It is the opposite of wet, upwelling gas in areas such as Jupiter's Great Red Spot or white ovals. On the other hand, it is unlike the dry and relatively cloudless feature into which the Galileo probe descended in 1995, because that region had the same temperatures as its surroundings and did not appear nearly as dark as this new spot.

The temperatures sampled by the photopolarimeter radiometer are near the top of Jupiter's troposphere, where wind motions control the atmosphere. The top row of arrows shows the location of temperature waves in a warm region of the atmosphere. These types of waves have never been seen before. What is interesting about these waves is both that they are 'channeled' within the warm band at the top of the panel, and that they appear to have no counterpart in the visible cloud structure. Thermal waves have already been seen in Jupiter that are independent of the cloud structure, but those waves were much larger in size. This is the first time Jupiter's temperatures have been mapped at a spatial resolution better than 2,000 kilometers (1,243 miles), allowing these waves to be detected.

These maps include an area on Jupiter between approximately the equator and 40 degrees south latitude, covering about 60 degrees of longitude. They were taken in late September during the spacecraft's 17th orbit.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC.

Cloud point extraction-flame atomic absorption spectrometry for pre-concentration and determination of trace amounts of silver ions in water samples.

PubMed

Yang, Xiupei; Jia, Zhihui; Yang, Xiaocui; Li, Gu; Liao, Xiangjun

2017-03-01

A cloud point extraction (CPE) method was used as a pre-concentration strategy prior to the determination of trace levels of silver in water by flame atomic absorption spectrometry (FAAS) The pre-concentration is based on the clouding phenomena of non-ionic surfactant, triton X-114, with Ag (I)/diethyldithiocarbamate (DDTC) complexes in which the latter is soluble in a micellar phase composed by the former. When the temperature increases above its cloud point, the Ag (I)/DDTC complexes are extracted into the surfactant-rich phase. The factors affecting the extraction efficiency including pH of the aqueous solution, concentration of the DDTC, amount of the surfactant, incubation temperature and time were investigated and optimized. Under the optimal experimental conditions, no interference was observed for the determination of 100 ng·mL -1 Ag + in the presence of various cations below their maximum concentrations allowed in this method, for instance, 50 μg·mL -1 for both Zn 2+ and Cu 2+ , 80 μg·mL -1 for Pb 2+ , 1000 μg·mL -1 for Mn 2+ , and 100 μg·mL -1 for both Cd 2+ and Ni 2+ . The calibration curve was linear in the range of 1-500 ng·mL -1 with a limit of detection (LOD) at 0.3 ng·mL -1 . The developed method was successfully applied for the determination of trace levels of silver in water samples such as river water and tap water.

LACIS-T - A humid wind tunnel for investigating the Interactions between Cloud Microphysics and Turbulence

NASA Astrophysics Data System (ADS)

Voigtländer, Jens; Niedermeier, Dennis; Siebert, Holger; Shaw, Raymond; Schumacher, Jörg; Stratmann, Frank

2017-04-01

To improve the fundamental and quantitative understanding of the interactions between cloud microphysical and turbulent processes, the Leibniz Institute for Tropospheric Research (TROPOS) has built up a new humid wind tunnel (LACIS-T). LACIS-T allows for the investigation of cloud microphysical processes, such as cloud droplet activation and freezing, under-well defined thermodynamic and turbulent flow conditions. It therewith allows for the straight forward continuation, extension, and completion of the cloud microphysics related investigations carried out at the Leipzig Aerosol Cloud Interaction Simulator (LACIS) under laminar flow conditions. Characterization of the wind tunnel with respect to flow, thermodynamics, and droplet microphysics is carried out with probes mounted inside (pitot tube and hot-wire anemometer for mean velocity and fluctuations, Pt100 sensor for mean temperature, cold-wire sensor for temperature fluctuations is in progress, as well as a dew-point mirror for mean water vapor concentration, a Lyman-alpha sensor for water vapor fluctuations is in progress) the measurement section, and from outside with optical detection methods (a laser light sheet is available for cloud droplet visualization, a digital holography system for detection of cloud droplet size distributions will be installed for tests in February 2017), respectively. Computational fluid dynamics (CFD) simulations have been carried out for defining suitable experimental conditions and assisting the interpretation of the experimental data. In this work, LACIS-T, its fundamental operating principle, and first preliminary results from ongoing characterization efforts will be presented.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

A shape-based segmentation method for mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen

2013-07-01

Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.

The enhancement and suppression of immersion mode heterogeneous ice-nucleation by solutes.

PubMed

Whale, Thomas F; Holden, Mark A; Wilson, Theodore W; O'Sullivan, Daniel; Murray, Benjamin J

2018-05-07

Heterogeneous nucleation of ice from aqueous solutions is an important yet poorly understood process in multiple fields, not least the atmospheric sciences where it impacts the formation and properties of clouds. In the atmosphere ice-nucleating particles are usually, if not always, mixed with soluble material. However, the impact of this soluble material on ice nucleation is poorly understood. In the atmospheric community the current paradigm for freezing under mixed phase cloud conditions is that dilute solutions will not influence heterogeneous freezing. By testing combinations of nucleators and solute molecules we have demonstrated that 0.015 M solutions (predicted melting point depression <0.1 °C) of several ammonium salts can cause suspended particles of feldspars and quartz to nucleate ice up to around 3 °C warmer than they do in pure water. In contrast, dilute solutions of certain alkali metal halides can dramatically depress freezing points for the same nucleators. At 0.015 M, solutes can enhance or deactivate the ice-nucleating ability of a microcline feldspar across a range of more than 10 °C, which corresponds to a change in active site density of more than a factor of 10 5 . This concentration was chosen for a survey across multiple solutes-nucleant combinations since it had a minimal colligative impact on freezing and is relevant for activating cloud droplets. Other nucleators, for instance a silica gel, are unaffected by these 'solute effects', to within experimental uncertainty. This split in response to the presence of solutes indicates that different mechanisms of ice nucleation occur on the different nucleators or that surface modification of relevance to ice nucleation proceeds in different ways for different nucleators. These solute effects on immersion mode ice nucleation may be of importance in the atmosphere as sea salt and ammonium sulphate are common cloud condensation nuclei (CCN) for cloud droplets and are internally mixed with ice-nucleating particles in mixed-phase clouds. In addition, we propose a pathway dependence where activation of CCN at low temperatures might lead to enhanced ice formation relative to pathways where CCN activation occurs at higher temperatures prior to cooling to nucleation temperature.

The enhancement and suppression of immersion mode heterogeneous ice-nucleation by solutes

PubMed Central

Holden, Mark A.; Wilson, Theodore W.; O'Sullivan, Daniel; Murray, Benjamin J.

2018-01-01

Heterogeneous nucleation of ice from aqueous solutions is an important yet poorly understood process in multiple fields, not least the atmospheric sciences where it impacts the formation and properties of clouds. In the atmosphere ice-nucleating particles are usually, if not always, mixed with soluble material. However, the impact of this soluble material on ice nucleation is poorly understood. In the atmospheric community the current paradigm for freezing under mixed phase cloud conditions is that dilute solutions will not influence heterogeneous freezing. By testing combinations of nucleators and solute molecules we have demonstrated that 0.015 M solutions (predicted melting point depression <0.1 °C) of several ammonium salts can cause suspended particles of feldspars and quartz to nucleate ice up to around 3 °C warmer than they do in pure water. In contrast, dilute solutions of certain alkali metal halides can dramatically depress freezing points for the same nucleators. At 0.015 M, solutes can enhance or deactivate the ice-nucleating ability of a microcline feldspar across a range of more than 10 °C, which corresponds to a change in active site density of more than a factor of 105. This concentration was chosen for a survey across multiple solutes–nucleant combinations since it had a minimal colligative impact on freezing and is relevant for activating cloud droplets. Other nucleators, for instance a silica gel, are unaffected by these ‘solute effects’, to within experimental uncertainty. This split in response to the presence of solutes indicates that different mechanisms of ice nucleation occur on the different nucleators or that surface modification of relevance to ice nucleation proceeds in different ways for different nucleators. These solute effects on immersion mode ice nucleation may be of importance in the atmosphere as sea salt and ammonium sulphate are common cloud condensation nuclei (CCN) for cloud droplets and are internally mixed with ice-nucleating particles in mixed-phase clouds. In addition, we propose a pathway dependence where activation of CCN at low temperatures might lead to enhanced ice formation relative to pathways where CCN activation occurs at higher temperatures prior to cooling to nucleation temperature. PMID:29780544

Cold column trapping-cloud point extraction coupled to high performance liquid chromatography for preconcentration and determination of curcumin in human urine.

PubMed

Rahimi, Marzieh; Hashemi, Payman; Nazari, Fariba

2014-05-15

A cold column trapping-cloud point extraction (CCT-CPE) method coupled to high performance liquid chromatography (HPLC) was developed for preconcentration and determination of curcumin in human urine. A nonionic surfactant, Triton X-100, was used as the extraction medium. In the proposed method, a low surfactant concentration of 0.4% v/v and a short heating time of only 2min at 70°C were sufficient for quantitative extraction of the analyte. For the separation of the extraction phase, the resulted cloudy solution was passed through a packed trapping column that was cooled to 0 °C. The temperature of the CCT column was then increased to 25°C and the surfactant rich phase was desorbed with 400μL ethanol to be directly injected into HPLC for the analysis. The effects of different variables such as pH, surfactant concentration, cloud point temperature and time were investigated and optimum conditions were established by a central composite design (response surface) method. A limit of detection of 0.066mgL(-1) curcumin and a linear range of 0.22-100mgL(-1) with a determination coefficient of 0.9998 were obtained for the method. The average recovery and relative standard deviation for six replicated analysis were 101.0% and 2.77%, respectively. The CCT-CPE technique was faster than a conventional CPE method requiring a lower concentration of the surfactant and lower temperatures with no need for the centrifugation. The proposed method was successfully applied to the analysis of curcumin in human urine samples. Copyright © 2014 Elsevier B.V. All rights reserved.

LSAH: a fast and efficient local surface feature for point cloud registration

NASA Astrophysics Data System (ADS)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

Meteorologial Techniques (Revision 21 Feb 2007)

DTIC Science & Technology

2003-06-13

Dissipation of Stratus Using Mixing Ratio and Temperature ------------------------- 2-12 Figure 2-27 Tropopause Method of Forecasting Cirrus...2-51 Figure 2-70 Bright Band Identification Using the WSR-88D...convective clouds using surface dew-point depressions --------------------- 2-11 Table 2-5 Aircraft category type

HCl in rocket exhaust clouds - Atmospheric dispersion, acid aerosol characteristics, and acid rain deposition

NASA Technical Reports Server (NTRS)

Pellett, G. L.; Sebacher, D. I.; Bendura, R. J.; Wornom, D. E.

1983-01-01

Both measurements and model calculations of the temporal dispersion of peak HCl (g + aq) concentration in Titan III exhaust clouds are found to be well characterized by one-term power-law decay expressions. The respective coefficients and decay exponents, however, are found to vary widely with meteorology. The HCl (g), HCl (g + aq), dewpoint, and temperature-pressure-altitude data for Titan III exhaust clouds are consistent with accurately calculated HCl/H2O vapor-liquid compositions for a model quasi-equilibrated flat surface aqueous aerosol. Some cloud evolution characteristics are also defined. Rapid and extensive condensation of aqueous acid clearly occurs during the first three min of cloud rise. Condensation is found to be intensified by the initial entrainment of relatively moist ambient air from lower levels, that is, from levels below eventual cloud stabilization. It is pointed out that if subsequent dilution air at stabilization altitude is significantly drier, a state of maximum condensation soon occurs, followed by an aerosol evaporation phase.

Formation of model polar stratospheric cloud films

NASA Technical Reports Server (NTRS)

Middlebrook, Ann M.; Koehler, Birgit G.; Mcneill, Laurie S.; Tolbert, Margaret A.

1992-01-01

Fourier transform infrared spectroscopy was used to examine the competitive growth of films representative of polar stratospheric clouds. These experiments show that either crystalline nitric acid trihydrate (beta-NAT) or amorphous films with H2O:HNO3 ratios close to 3:1 formed at temperatures 3-7 K warmer than the ice frost point under stratospheric pressure conditions. In addition, with higher HNO3 pressure, we observed nitric acid dihydrate (NAD) formation at temperatures warmer than ice formation. However, our experiments also show that NAD surfaces converted to beta-NAT upon exposure to stratospheric water pressures. Finally, we determined that the net uptake coefficient for HNO3 on beta-NAT is close to unity, whereas the net uptake coefficient for H2O is much less.

A Review of Spatial and Seasonal Changes in Condensation Clouds Observed During Aerobraking by MGS TES

NASA Technical Reports Server (NTRS)

Pearl, J. C.; Smith, M. D.; Conrath, B. J.; Bandfield, J. L.; Christensen, P. R.

1999-01-01

Successful operation of the Mars Global Surveyor spacecraft beginning in September 1997, has permitted extensive infrared observations of condensation clouds during the martian southern summer and fall seasons (184 deg

The variability of California summertime marine stratus: impacts on surface air temperatures

USGS Publications Warehouse

Iacobellis, Sam F.; Cayan, Daniel R.

2013-01-01

This study investigates the variability of clouds, primarily marine stratus clouds, and how they are associated with surface temperature anomalies over California, especially along the coastal margin. We focus on the summer months of June to September when marine stratus are the dominant cloud type. Data used include satellite cloud reflectivity (cloud albedo) measurements, hourly surface observations of cloud cover and air temperature at coastal airports, and observed values of daily surface temperature at stations throughout California and Nevada. Much of the anomalous variability of summer clouds is organized over regional patterns that affect considerable portions of the coast, often extend hundreds of kilometers to the west and southwest over the North Pacific, and are bounded to the east by coastal mountains. The occurrence of marine stratus is positively correlated with both the strength and height of the thermal inversion that caps the marine boundary layer, with inversion base height being a key factor in determining their inland penetration. Cloud cover is strongly associated with surface temperature variations. In general, increased presence of cloud (higher cloud albedo) produces cooler daytime temperatures and warmer nighttime temperatures. Summer daytime temperature fluctuations associated with cloud cover variations typically exceed 1°C. The inversion-cloud albedo-temperature associations that occur at daily timescales are also found at seasonal timescales.

Convective Cloud Towers and Precipitation Initiation, Frequency and Intensity

NASA Astrophysics Data System (ADS)

Vant-hull, B.; Mahani, S. E.; Autones, F.; Rabin, R.; Mecikalski, J. R.; Khanbilvardi, R.

2012-12-01

: Geosynchronous satellite retrieval of precipitation is desirable because it would provide continuous observation throughout most of the globe in regions where radar data is not available. In the current work the distribution of precipitation rates is examined as a function of cloud tower area and cloud top temperature. A thunderstorm tracking algorithm developed at Meteo-France is used to track cumulus towers that are matched up with radar data at 5 minute 1 km resolution. It is found that roughly half of the precipitation occurs in the cloud mass that surrounds the towers, and when a tower is first detected the precipitation is already in progress 50% of the time. The average density of precipitation per area is greater as the towers become smaller and colder, yet the averaged shape of the precipitation intensity distribution is remarkably constant in all convective situations with cloud tops warmer than 220 K. This suggests that on average all convective precipitation events look the same, unaffected by the higher frequency of occurrence per area inside the convective towers. Only once the cloud tops are colder than 220 K does the precipitation intensity distribution become weighted towards higher instantaneous intensities. Radar precipitation shown in shades of green to blue, lightning in orange; black diamonds are coldest points in each tower. Ratio of number of pixels of given precipitation inside versus outside the convective towers, for various average cloud top temperatures. A flat plot indicates the distribution of rainfall inside and outside the towers has the same shape.

Derivation of Cloud Heating Rate Profiles using observations of Mixed-Phase Arctic Clouds: Impacts of Solar Zenith Angle

NASA Astrophysics Data System (ADS)

Zhang, G.; McFarquhar, G.; Poellot, M.; Verlinde, J.; Heymsfield, A.; Kok, G.

2005-12-01

Arctic stratus clouds play an important role in the energy balance of the Arctic region. Previous studies have suggested that Arctic stratus persist due to a balance among cloud top radiation cooling, latent heating, ice crystal fall out and large scale forcing. In this study, radiative heating profiles through Arctic stratus are computed using cloud, surface and thermodynamic observations obtained during the Mixed-Phase Arctic Cloud Experiment (M-PACE) as input to the radiative transfer model STREAMER. In particular, microphysical and macrophycial cloud properties such as phase, water content, effective particle size, particle shape, cloud height and cloud thickness were derived using data collected by in-situ sensors on the University of North Dakota (UND) Citation and ground-based remote sensors at Barrow and Oliktok Point. Temperature profiles were derived from radiosonde launches and a fresh snow surface was assumed. One series of sensitivity studies explored the dependence of the heating profile on the solar zenith angle. For smaller solar zenith angles, more incoming solar radiation is received at cloud top acting to counterbalance infrared cooling. As solar zenith angle in the Arctic is large compared to low latitudes, a large solar zenith angle may contribute to the longevity of these clouds.

Molecules in interstellar clouds. [physical and chemical conditions of star formation and biological evolution

NASA Technical Reports Server (NTRS)

Irvine, W. M.; Hjalmarson, A.; Rydbeck, O. E. H.

1981-01-01

The physical conditions and chemical compositions of the gas in interstellar clouds are reviewed in light of the importance of interstellar clouds for star formation and the origin of life. The Orion A region is discussed as an example of a giant molecular cloud where massive stars are being formed, and it is pointed out that conditions in the core of the cloud, with a kinetic temperature of about 75 K and a density of 100,000-1,000,000 molecules/cu cm, may support gas phase ion-molecule chemistry. The Taurus Molecular Clouds are then considered as examples of cold, dark, relatively dense interstellar clouds which may be the birthplaces of solar-type stars and which have been found to contain the heaviest interstellar molecules yet discovered. The molecular species identified in each of these regions are tabulated, including such building blocks of biological monomers as H2O, NH3, H2CO, CO, H2S, CH3CN and H2, and more complex species such as HCOOCH3 and CH3CH2CN.

Deep Convective Cloud Top Heights and Their Thermodynamic Control During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Sherwood, Steven C.; Minnis, Patrick; McGill, Matthew

2004-01-01

Infrared (11 micron) radiances from GOES-8 and local radiosonde profiles, collected during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) in July 2002, are used to assess the vertical distribution of Florida-area deep convective cloud top height and test predictions as to its variation based on parcel theory. The highest infrared tops (Z(sub 11)) reached approximately to the cold point, though there is at least a 1-km uncertainty due to unknown cloud-environment temperature differences. Since lidar shows that visible 'tops' are 1 km or more above Z(sub 11), visible cloud tops frequently penetrated the lapse-rate tropopause (approx. 15 km). Further, since lofted ice content may be present up to approx. 1 km above the visible tops, lofting of moisture through the mean cold point (15.4 km) was probably common. Morning clouds, and those near Key West, rarely penetrated the tropopause. Non-entraining parcel theory (i.e., CAPE) does not successfully explain either of these results, but can explain some of the day-to-day variations in cloud top height over the peninsula. Further, moisture variations above the boundary layer account for most of the day-today variability not explained by CAPE, especially over the oceans. In all locations, a 20% increase in mean mixing ratio between 750 and 500 hPa was associated with about 1 km deeper maximum cloud penetration relative to the neutral level. These results suggest that parcel theory may be useful for predicting changes in cumulus cloud height over time, but that parcel entrainment must be taken into account even for the tallest clouds. Accordingly, relative humidity above the boundary layer may exert some control on the height of the tropical troposphere.

A physically based algorithm for non-blackbody correction of the cloud top temperature for the convective clouds

NASA Astrophysics Data System (ADS)

Wang, C.; Luo, Z. J.; Chen, X.; Zeng, X.; Tao, W.; Huang, X.

2012-12-01

Cloud top temperature is a key parameter to retrieval in the remote sensing of convective clouds. Passive remote sensing cannot directly measure the temperature at the cloud tops. Here we explore a synergistic way of estimating cloud top temperature by making use of the simultaneous passive and active remote sensing of clouds (in this case, CloudSat and MODIS). Weighting function of the MODIS 11μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat retrievals and temperature and humidity profiles based on ECMWF ERA-interim reanalysis into a radiation transfer model. Among 19,699 tropical deep convective clouds observed by the CloudSat in 2008, the averaged effective emission level (EEL, where the weighting function attains its maximum) is at optical depth 0.91 with a standard deviation of 0.33. Furthermore, the vertical gradient of CloudSat radar reflectivity, an indicator of the fuzziness of convective cloud top, is linearly proportional to, d_{CTH-EEL}, the distance between the EEL of 11μm channel and cloud top height (CTH) determined by the CloudSat when d_{CTH-EEL}<0.6km. Beyond 0.6km, the distance has little sensitivity to the vertical gradient of CloudSat radar reflectivity. Based on these findings, we derive a formula between the fuzziness in the cloud top region, which is measurable by CloudSat, and the MODIS 11μm brightness temperature assuming that the difference between effective emission temperature and the 11μm brightness temperature is proportional to the cloud top fuzziness. This formula is verified using the simulated deep convective cloud profiles by the Goddard Cumulus Ensemble model. We further discuss the application of this formula in estimating cloud top buoyancy as well as the error characteristics of the radiative calculation within such deep-convective clouds.

Temperature as a third dimension in column-density mapping of dusty astrophysical structures associated with star formation

NASA Astrophysics Data System (ADS)

Marsh, K. A.; Whitworth, A. P.; Lomax, O.

2015-12-01

We present point process mapping (PPMAP), a Bayesian procedure that uses images of dust continuum emission at multiple wavelengths to produce resolution-enhanced image cubes of differential column density as a function of dust temperature and position. PPMAP is based on the generic `point process formalism, whereby the system of interest (in this case, a dusty astrophysical structure such as a filament or pre-stellar core) is represented by a collection of points in a suitably defined state space. It can be applied to a variety of observational data, such as Herschel images, provided only that the image intensity is delivered by optically thin dust in thermal equilibrium. PPMAP takes full account of the instrumental point-spread functions and does not require all images to be degraded to the same resolution. We present the results of testing using simulated data for a pre-stellar core and a fractal turbulent cloud, and demonstrate its performance with real data from the Herschel infrared Galactic Plane Survey (Hi-GAL). Specifically, we analyse observations of a large filamentary structure in the CMa OB1 giant molecular cloud. Histograms of differential column density indicate that the warm material (T ≳ 13 K) is distributed lognormally, consistent with turbulence, but the column densities of the cooler material are distributed as a high-density tail, consistent with the effects of self-gravity. The results illustrate the potential of PPMAP to aid in distinguishing between different physical components along the line of sight in star-forming clouds, and aid the interpretation of the associated Probability distribution functions (PDFs) of column density.

Analysis of the Meteorology Associated with the 1998 NASA Glenn Twin Otter Icing Flights

NASA Technical Reports Server (NTRS)

Bernstein, Ben C.

2000-01-01

This document contains a basic analysis of the meteorology associated with the NASA Glenn Twin Otter icing encounters between December 1997 and March 1998. The purpose of this analysis is to provide a meteorological context for the aircraft data collected during these flights. For each case, the following data elements are presented: (1) A brief overview of the Twin Otter encounter, including locations, liquid water contents, temperatures and microphysical makeup of the clouds and precipitation aloft, (2) Upper-air charts, providing hand-analyzed locations of lows, troughs, ridges, saturated/unsaturated air, temperatures, warm/cold advection, and jet streams, (3) Balloon-borne soundings, providing vertical profiles of temperature, moisture and winds, (4) Infrared and visible satellite data, providing cloud locations and cloud top temperature, (5) 3-hourly surface charts, providing hand-analyzed locations of lows, highs, fronts, precipitation (including type) and cloud cover, (6) Hourly, regional radar mosaics, providing fine resolution of the locations of precipitation (including intensity and type), pilot reports of icing (including intensity and type), surface observations of precipitation type and Twin Otter tracks for a one hour window centered on the time of the radar data, and (7) Hourly plots of icing pilot reports, providing the icing intensity, icing type, icing altitudes and aircraft type. Outages occurred in nearly every dataset at some point. All relevant data that was available is presented here. All times are in UTC and all heights are in feet above mean sea level (MSL).

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.

Solubilization of flurbiprofen within non-ionic Tween 20 surfactant micelles: a 19F and 1H NMR study.

PubMed

Saveyn, Pieter; Cocquyt, Ellen; Zhu, Wuxin; Sinnaeve, Davy; Haustraete, Katrien; Martins, José C; Van der Meeren, Paul

2009-07-14

The solubilization of the poorly water soluble anti-inflammatory drug flurbiprofen in non-ionic Tween 20 surfactant micellar solutions was studied by both (19)F and (1)H NMR spectroscopy in an acidic environment. These non-destructive techniques allowed us to investigate the effect of temperature cycling in situ. Using (19)F NMR, an increased solubilisation capacity was observed as the temperature increased. This effect became more pronounced above the cloud point, which was reduced by more than 30 degrees C in the presence of an excess of flurbiprofen. Upon clouding, peak splitting was observed in the (19)F spectrum, which indicates that two pools of solubilised flurbiprofen exist that are in slow exchange on the NMR frequency timescale. The clouding and solubilization processes were found to be reversible, albeit with slow kinetics. Based on chemical shift differences of both Tween 20 and flurbiprofen, as well as NOESY experiments, the flurbiprofen was found to be accumulated within the palisade layer of the Tween 20 micelles.

Applicability Analysis of Cloth Simulation Filtering Algorithm for Mobile LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Cai, S.; Zhang, W.; Qi, J.; Wan, P.; Shao, J.; Shen, A.

2018-04-01

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

Investigating the Accuracy of Point Clouds Generated for Rock Surfaces

NASA Astrophysics Data System (ADS)

Seker, D. Z.; Incekara, A. H.

2016-12-01

Point clouds which are produced by means of different techniques are widely used to model the rocks and obtain the properties of rock surfaces like roughness, volume and area. These point clouds can be generated by applying laser scanning and close range photogrammetry techniques. Laser scanning is the most common method to produce point cloud. In this method, laser scanner device produces 3D point cloud at regular intervals. In close range photogrammetry, point cloud can be produced with the help of photographs taken in appropriate conditions depending on developing hardware and software technology. Many photogrammetric software which is open source or not currently provide the generation of point cloud support. Both methods are close to each other in terms of accuracy. Sufficient accuracy in the mm and cm range can be obtained with the help of a qualified digital camera and laser scanner. In both methods, field work is completed in less time than conventional techniques. In close range photogrammetry, any part of rock surfaces can be completely represented owing to overlapping oblique photographs. In contrast to the proximity of the data, these two methods are quite different in terms of cost. In this study, whether or not point cloud produced by photographs can be used instead of point cloud produced by laser scanner device is investigated. In accordance with this purpose, rock surfaces which have complex and irregular shape located in İstanbul Technical University Ayazaga Campus were selected as study object. Selected object is mixture of different rock types and consists of both partly weathered and fresh parts. Study was performed on a part of 30m x 10m rock surface. 2D and 3D analysis were performed for several regions selected from the point clouds of the surface models. 2D analysis is area-based and 3D analysis is volume-based. Analysis conclusions showed that point clouds in both are similar and can be used as alternative to each other. This proved that point cloud produced using photographs which are both economical and enables to produce data in less time can be used in several studies instead of point cloud produced by laser scanner.

Absorption of Solar Radiation by Clouds: A Second Look at Irradiance Measurements

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; King, Michael D.; Cahalan, Robert F.; Lau, William K.-M. (Technical Monitor)

2001-01-01

A decade ago, Stephens and Tsay provided an overview of the subject of absorption of solar radiation by clouds in the earth's atmosphere. They summarized the available evidence that pointed to disagreements between theoretical and observed values of cloud absorption (and reflection). At that time, a theoretician's approach (assuming perfect flux measurements) was adopted to test the model uncertainty under various hypotheses, such as the omitted large drops, excess absorbing aerosols, enhanced water vapor continuum absorption, and cloud inhomogeneity. Since then, several advances in theoretical work have been made, but a satisfactory answer for the discrepancy is still lacking. Now, we offer an experimentalist's approach (focusing on field, not laboratory) to examine the observational uncertainty under numerous field factors, such as the temperature dependence, attitude control, and sampling strategy in the spatial and spectral domain. Examples from recent field campaigns have pointed out that these sources of error may be responsible for the unacceptable level of uncertainty (e.g., as large as 20 W/square m). We give examples of each, discuss their contribution to overall uncertainty in shortwave absorption, and suggest a coordinated approach to their solution.

Determination of ultra-trace aluminum in human albumin by cloud point extraction and graphite furnace atomic absorption spectrometry.

PubMed

Sun, Mei; Wu, Qianghua

2010-04-15

A cloud point extraction (CPE) method for the preconcentration of ultra-trace aluminum in human albumin prior to its determination by graphite furnace atomic absorption spectrometry (GFAAS) had been developed in this paper. The CPE method was based on the complex of Al(III) with 1-(2-pyridylazo)-2-naphthol (PAN) and Triton X-114 was used as non-ionic surfactant. The main factors affecting cloud point extraction efficiency, such as pH of solution, concentration and kind of complexing agent, concentration of non-ionic surfactant, equilibration temperature and time, were investigated in detail. An enrichment factor of 34.8 was obtained for the preconcentration of Al(III) with 10 mL solution. Under the optimal conditions, the detection limit of Al(III) was 0.06 ng mL(-1). The relative standard deviation (n=7) of sample was 3.6%, values of recovery of aluminum were changed from 92.3% to 94.7% for three samples. This method is simple, accurate, sensitive and can be applied to the determination of ultra-trace aluminum in human albumin. 2009 Elsevier B.V. All rights reserved.

Cloud point extraction and diffuse reflectance-Fourier transform infrared spectroscopic determination of chromium(VI): A probe to adulteration in food stuffs.

PubMed

Tiwari, Swapnil; Deb, Manas Kanti; Sen, Bhupendra K

2017-04-15

A new cloud point extraction (CPE) method for the determination of hexavalent chromium i.e. Cr(VI) in food samples is established with subsequent diffuse reflectance-Fourier transform infrared (DRS-FTIR) analysis. The method demonstrates enrichment of Cr(VI) after its complexation with 1,5-diphenylcarbazide. The reddish-violet complex formed showed λ max at 540nm. Micellar phase separation at cloud point temperature of non-ionic surfactant, Triton X-100 occurred and complex was entrapped in surfactant and analyzed using DRS-FTIR. Under optimized conditions, the limit of detection (LOD) and quantification (LOQ) were 1.22 and 4.02μgmL -1 , respectively. Excellent linearity with correlation coefficient value of 0.94 was found for the concentration range of 1-100μgmL -1 . At 10μgmL -1 the standard deviation for 7 replicate measurements was found to be 0.11μgmL -1 . The method was successfully applied to commercially marketed food stuffs, and good recoveries (81-112%) were obtained by spiking the real samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

LiDAR Point Cloud and Stereo Image Point Cloud Fusion

DTIC Science & Technology

2013-09-01

LiDAR point cloud (right) highlighting linear edge features ideal for automatic registration...point cloud (right) highlighting linear edge features ideal for automatic registration. Areas where topography is being derived, unfortunately, do...with the least amount of automatic correlation errors was used. The following graphic (Figure 12) shows the coverage of the WV1 stereo triplet as

LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings

NASA Astrophysics Data System (ADS)

Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan

2018-01-01

This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system

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

Liu, Wenyang; Cheung, Yam; Sawant, Amit

2016-05-15

Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparsemore » regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.« less

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system.

PubMed

Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan

2016-05-01

To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system

PubMed Central

Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan

2016-01-01

Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications. PMID:27147347

Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm

PubMed Central

Yan, Li; Xie, Hong; Chen, Changjun

2017-01-01

Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%. PMID:28850100

Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm.

PubMed

Yan, Li; Tan, Junxiang; Liu, Hua; Xie, Hong; Chen, Changjun

2017-08-29

Registration of point clouds is a fundamental issue in Light Detection and Ranging (LiDAR) remote sensing because point clouds scanned from multiple scan stations or by different platforms need to be transformed to a uniform coordinate reference frame. This paper proposes an efficient registration method based on genetic algorithm (GA) for automatic alignment of two terrestrial LiDAR scanning (TLS) point clouds (TLS-TLS point clouds) and alignment between TLS and mobile LiDAR scanning (MLS) point clouds (TLS-MLS point clouds). The scanning station position acquired by the TLS built-in GPS and the quasi-horizontal orientation of the LiDAR sensor in data acquisition are used as constraints to narrow the search space in GA. A new fitness function to evaluate the solutions for GA, named as Normalized Sum of Matching Scores, is proposed for accurate registration. Our method is divided into five steps: selection of matching points, initialization of population, transformation of matching points, calculation of fitness values, and genetic operation. The method is verified using a TLS-TLS data set and a TLS-MLS data set. The experimental results indicate that the RMSE of registration of TLS-TLS point clouds is 3~5 mm, and that of TLS-MLS point clouds is 2~4 cm. The registration integrating the existing well-known ICP with GA is further proposed to accelerate the optimization and its optimizing time decreases by about 50%.

An LTE effective temperature scale for red supergiants in the Magellanic clouds

NASA Astrophysics Data System (ADS)

Tabernero, H. M.; Dorda, R.; Negueruela, I.; González-Fernández, C.

2018-05-01

We present a self-consistent study of cool supergiants (CSGs) belonging to the Magellanic clouds. We calculated stellar atmospheric parameters using LTE KURUCZ and MARCS atmospheric models for more than 400 individual targets by fitting a careful selection of weak metallic lines. We explore the existence of a Teff scale and its implications in two different metallicity environments (each Magellanic cloud). Critical and in-depth tests have been performed to assess the reliability of our stellar parameters (i.e. internal error budget, NLTE systematics). In addition, several Monte Carlo tests have been carried out to infer the significance of the Teff scale found. Our findings point towards a unique Teff scale that seems to be independent of the environment.

Automatic Classification of Trees from Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2015-08-01

Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into 'tree' and 'non-tree' classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the 'tree' or 'non-tree' class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

NASA Astrophysics Data System (ADS)

Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

2016-10-01

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

NASA Technical Reports Server (NTRS)

Welch, Ronald M.

1993-01-01

A series of cloud and sea ice retrieval algorithms are being developed in support of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Science Team objectives. These retrievals include the following: cloud fractional area, cloud optical thickness, cloud phase (water or ice), cloud particle effective radius, cloud top heights, cloud base height, cloud top temperature, cloud emissivity, cloud 3-D structure, cloud field scales of organization, sea ice fractional area, sea ice temperature, sea ice albedo, and sea surface temperature. Due to the problems of accurately retrieving cloud properties over bright surfaces, an advanced cloud classification method was developed which is based upon spectral and textural features and artificial intelligence classifiers.

Cloud Point Extraction for Electroanalysis: Anodic Stripping Voltammetry of Cadmium

PubMed Central

Rusinek, Cory A.; Bange, Adam; Papautsky, Ian; Heineman, William R.

2016-01-01

Cloud point extraction (CPE) is a well-established technique for the pre-concentration of hydrophobic species from water without the use of organic solvents. Subsequent analysis is then typically performed via atomic absorption spectroscopy (AAS), UV-Vis spectroscopy, or high performance liquid chromatography (HPLC). However, the suitability of CPE for electroanalytical methods such as stripping voltammetry has not been reported. We demonstrate the use of CPE for electroanalysis using the determination of cadmium (Cd2+) by anodic stripping voltammetry (ASV) as a representative example. Rather than using the chelating agents which are commonly used in CPE to form a hydrophobic, extractable metal complex, we used iodide and sulfuric acid to neutralize the charge on Cd2+ to form an extractable ion pair. Triton X-114 was chosen as the surfactant for the extraction because its cloud point temperature is near room temperature (22–25° C). Bare glassy carbon (GC), bismuth-coated glassy carbon (Bi-GC), and mercury-coated glassy carbon (Hg-GC) electrodes were compared for the CPE-ASV. A detection limit for Cd2+ of 1.7 nM (0.2 ppb) was obtained with the Hg-GC electrode. Comparison of ASV analysis without CPE was also investigated and a 20x decrease (4.0 ppb) in the detection limit was observed. The suitability of this procedure for the analysis of tap and river water samples was also demonstrated. This simple, versatile, environmentally friendly and cost-effective extraction method is potentially applicable to a wide variety of transition metals and organic compounds that are amenable to detection by electroanalytical methods. PMID:25996561

Water Ice Clouds and Dust in the Martian Atmosphere Observed by Mars Climate Sounder

NASA Technical Reports Server (NTRS)

Benson, Jennifer L.; Kass, David; Heavens, Nicholas; Kleinbohl, Armin

2011-01-01

The water ice clouds are primarily controlled by the temperature structure and form at the water condensation level. Clouds in all regions presented show day/night differences. Cloud altitude varies between night and day in the SPH and tropics: (1) NPH water ice opacity is greater at night than day at some seasons (2) The diurnal thermal tide controls the daily variability. (3) Strong day/night changes indicate that the amount of gas in the atmosphere varies significantly. See significant mixtures of dust and ice at the same altitude planet-wide (1) Points to a complex radiative and thermal balance between dust heating (in the visible) and ice heating or cooling in the infrared. Aerosol layering: (1) Early seasons reveal a zonally banded spatial distribution (2) Some localized longitudinal structure of aerosol layers (3) Later seasons show no consistent large scale organization

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

NASA Astrophysics Data System (ADS)

Cura, Rémi; Perret, Julien; Paparoditis, Nicolas

2017-05-01

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

Particle backscatter and relative humidity measured across cirrus clouds and comparison with state-of-the-art cirrus modelling

NASA Astrophysics Data System (ADS)

Brabec, M.; Wienhold, F. G.; Luo, B.; Vömel, H.; Immler, F.; Steiner, P.; Peter, T.

2012-04-01

Advanced measurement and modelling techniques are employed to determine the partitioning of atmospheric water between the gas phase and the condensed phase in and around cirrus clouds, and thus to identify in-cloud and out-of-cloud supersaturations with respect to ice. In November 2008 the newly developed balloon-borne backscatter sonde COBALD (Compact Optical Backscatter and AerosoL Detector) was flown 14 times together with a CFH (Cryogenic Frost point Hygrometer) from Lindenberg, Germany (52° N, 14° E). The case discussed here in detail shows two cirrus layers with in-cloud relative humidities with respect to ice between 50% and 130%. Global operational analysis data of ECMWF (roughly 1° × 1° horizontal and 1 km vertical resolution, 6-hourly stored fields) fail to represent ice water contents and relative humidities. Conversely, regional COSMO-7 forecasts (6.6 km × 6.6 km, 5-min stored fields) capture the measured humidities and cloud positions remarkably well. The main difference between ECMWF and COSMO data is the resolution of small-scale vertical features responsible for cirrus formation. Nevertheless, ice water contents in COSMO-7 are still off by factors 2-10, likely reflecting limitations in COSMO's ice phase bulk scheme. Significant improvements can be achieved by comprehensive size-resolved microphysical and optical modelling along backward trajectories based on COSMO-7 wind and temperature fields, which allow accurate computation of humidities, ice particle size distributions and backscatter ratios at the COBALD wavelengths. However, only by superimposing small-scale temperature fluctuations, which remain unresolved by the NWP models, can we obtain a satisfying agreement with the observations and reconcile the measured in-cloud non-equilibrium humidities with conventional ice cloud microphysics.

Extended Edited Synoptic Cloud Reports from Ships and Land Stations Over the Globe, 1952-2009 (NDP-026C)

DOE Data Explorer

Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington; Eastman, R.

1999-08-01

This database contains surface synoptic weather reports for the entire globe, gathered from various available data sets. The reports were processed, edited, and rewritten to provide a single dataset of individual observations of clouds, spanning the 57 years 1952-2008 for ship data and the 39 years 1971-2009 for land station data. In addition to the cloud portion of the synoptic report, each edited report also includes the associated pressure, present weather, wind, air temperature, and dew point (and sea surface temperature over oceans). This data set is called the "Extended Edited Cloud Report Archive" (EECRA). The EECRA is based solely on visual cloud observations from weather stations, reported in the WMO synoptic code (WMO, 1974). Reports must contain cloud-type information to be included in the archive. Past data sources include those from the Fleet Numerical Oceanographic Center (FNOC, 1971-1976) and the National Centers for Environmental Prediction (NCEP, 1977-1996). This update uses data from a new source, the 'Integrated Surface Database' (ISD, 1997-2009; Smith et al., 2011). Our past analyses of the EECRA identified a subset of 5388 weather stations that were determined to produce reliable day and night observations of cloud amount and type. The update contains observations only from this subset of stations. Details concerning processing, previous problems, contents, and comments are available in the archive's original documentation . The EECRA contains about 81 million cloud observations from ships and 380 million from land stations. The data files have been compressed using unix. Unix/linux users can "uncompress" or "gunzip" the files after downloading. If you're interested in the NDP-026C database, then you'll also want to explore its related data products, NDP-026D and NDP-026E.

A Review of Spatial and Seasonal Changes in Condensation Clouds Observed During Aerobraking by MGS TES

NASA Technical Reports Server (NTRS)

Pearl, J. C.; Smith, M. D.; Conrath, B. J.; Bandfield, J. L.; Christensen, P. R.

1999-01-01

Successful operation of the Mars Global Surveyor spacecraft, beginning in September 1997, has permitted extensive infrared observations of condensation clouds during the martian southern summer and fall seasons (184 deg less than L(sub s) less than 28 deg). Initially, thin (normal optical depth less than 0.06 at 825/ cm) ice clouds and hazes were widespread, showing a latitudinal gradient. With the onset of a regional dust storm at L(sub s) = 224 deg, ice clouds essentially vanished in the southern hemisphere, to reappear gradually after the decay of the storm. The thickest clouds (optical depth approx. 0.6) were associated with major volcanic features. At L(exp s) = 318 deg, the cloud at Ascraeus Mons was observed to disappear between 21:30 and 09:30, consistent with historically recorded diurnal behavior for clouds of this type. Limb observations showed extended optically thin (depth less than 0.04) stratiform clouds at altitudes up to 55 km. A water ice haze was present in the north polar night at altitudes up to 40 km; this probably provided heterogeneous nucleation sites for the formation of CO2 clouds at altitudes below the 1 mbar pressure level, where atmospheric temperatures dropped to the condensation point of CO2.

The initial giant umbrella cloud of the May 18th, 1980, explosive eruption of Mount St. Helens

USGS Publications Warehouse

Sparks, R.S.J.; Moore, J.G.; Rice, C.J.

1986-01-01

The initial eruption column of May 18th, 1980 reached nearly 30 km altitude and released 1017 joules of thermal energy into the atmosphere in only a few minutes. Ascent of the cloud resulted in forced intrusion of a giant umbrella-shaped cloud between altitudes of 10 and 20 km at radial horizontal velocities initially in excess of 50 m/s. The mushroom cloud expanded 15 km upwind, forming a stagnation point where the radial expansion velocity and wind velocity were equal. The cloud was initiated when the pyroclastic blast flow became buoyant. The flow reduced its density as it moved away from the volcano by decompression, by sedimentation, and by mixing with and heating the surrounding air. Observations indicate that much of the flow, covering an area of 600 km2, became buoyant within 1.5 minutes and abruptly ascended to form the giant cloud. Calculations are presented for the amount of air that must have been entrained into the flow to make it buoyant. Assuming an initial temperature of 450??C and a magmatic origin for the explosion, these calculations indicate that the flow became buoyant when its temperature was approximately 150??C and the flow consisted of a mixture of 3.25 ?? 1011 kg of pyroclasts and 5.0 ?? 1011 kg of air. If sedimentation is considered, these figures reduce to 1.1 ?? 1011 kg of pyroclasts and 1.0 ?? 1011 kg of air. ?? 1986.

Jupiter's Multi-level Clouds

NASA Technical Reports Server (NTRS)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.

By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.

The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity, while yellowish regions at temperate latitudes may indicate tropospheric clouds with small particles which also allow leakage. A mix of high and low-altitude aerosols causes the aqua appearance of the Great Red Spot and equatorial region.

The Jet Propulsion Laboratory manages the Galileo mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web Galileo mission home page at http://galileo.jpl.nasa.gov.

Fast calculation method of computer-generated hologram using a depth camera with point cloud gridding

NASA Astrophysics Data System (ADS)

Zhao, Yu; Shi, Chen-Xiao; Kwon, Ki-Chul; Piao, Yan-Ling; Piao, Mei-Lan; Kim, Nam

2018-03-01

We propose a fast calculation method for a computer-generated hologram (CGH) of real objects that uses a point cloud gridding method. The depth information of the scene is acquired using a depth camera and the point cloud model is reconstructed virtually. Because each point of the point cloud is distributed precisely to the exact coordinates of each layer, each point of the point cloud can be classified into grids according to its depth. A diffraction calculation is performed on the grids using a fast Fourier transform (FFT) to obtain a CGH. The computational complexity is reduced dramatically in comparison with conventional methods. The feasibility of the proposed method was confirmed by numerical and optical experiments.

Calibration and Field Deployment of the NSF G-V VCSEL Hygrometer

NASA Astrophysics Data System (ADS)

DiGangi, J. P.; O'Brien, A.; Diao, M.; Hamm, C.; Zhang, Q.; Beaton, S. P.; Zondlo, M. A.

2012-12-01

Cloud formation and dynamics have a significant influence on the Earth's radiative forcing budget, which illustrates the importance of clouds with respect to global climate. Therefore, an accurate understanding of the microscale processes dictating cloud formation is crucial for accurate computer modeling of global climate change. A critical tool for understanding these processes from an airborne platform is an instrument capable of measuring water vapor with both high accuracy and time, thus spatial, resolution. Our work focuses on an open-path, compact, vertical-cavity surface-emitting laser (VCSEL) absorption-based hygrometer, capable of 25 Hz temporal resolution, deployed on the NSF/NCAR Gulfstream-V aircraft platform. The open path nature of our instrument also helps to minimize sampling artifacts. We will discuss our efforts toward achieving within 5% accuracy over 5 orders of magnitude of water vapor concentrations. This involves an intercomparison of five independent calibration methods: ice surface saturators using an oil temperature bath, solvent slush baths (e.g. chloroform/LN2, water/ice), a research-grade frost point hygrometer, static pressure experiments, and Pt catalyzed hydrogen gas. This wide variety of available tools allows us to accurately constrain the calibrant water vapor concentrations both before and after the VCSEL hygrometer sampling chamber. For example, the mixing ratio as measured by research-grade frost point hygrometer after the VCSEL hygrometer agreed within 2% of the mixing ration expected from the water/ice bubbler source before the VCSEL over the temperature range -50°C to 20°C. Finally, due to the compact nature of our instrument, we are able to perform these calibrations simultaneously at the same temperatures (-80°C to 30°C) and pressures (150 mbar to 760 mbar) as sampled ambient air during a flight. This higher accuracy can significantly influence the science utilizing this data, which we will illustrate using preliminary data from our most recent field deployment, the NSF Deep Convective Clouds and Chemistry Experiment in May-June 2012

Analysis and forecast experiments incorporating satellite soundings and cloud and water vapor drift wind information

NASA Technical Reports Server (NTRS)

Goodman, Brian M.; Diak, George R.; Mills, Graham A.

1986-01-01

A system for assimilating conventional meteorological data and satellite-derived data in order to produce four-dimensional gridded data sets of the primary atmospheric variables used for updating limited area forecast models is described. The basic principles of a data assimilation scheme as proposed by Lorenc (1984) are discussed. The design of the system and its incremental assimilation cycles are schematically presented. The assimilation system was tested using radiosonde, buoy, VAS temperature, dew point, gradient wind data, cloud drift, and water vapor motion data. The rms vector errors for the data are analyzed.

Analysis of the Meteorology Associated with the 1997 NASA Glenn Twin Otter Icing Events

NASA Technical Reports Server (NTRS)

Bernstein, Ben C.

2000-01-01

This part of the document contains an analysis of the meteorology associated with the premier icing encounters from the January-March 1997 NASA Twin Otter dataset. The purpose of this analysis is to provide a meteorological context for the aircraft data collected during these flights. For each case, the following data elements are presented: (1) A detailed discussion of the Twin Otter encounter, including locations, liquid water contents, temperatures and microphysical makeup of the clouds and precipitation aloft, (2) Upper-air charts, providing hand-analyzed locations of lows, troughs, ridges, saturated/unsaturated air, temperatures, warm/cold advection, and jet streams, (3) Balloon-borne soundings, providing vertical profiles of temperature, moisture and winds, (4) Infrared satellite data, providing cloud locations and cloud top temperature, (5) 3-hourly surface charts, providing hand-analyzed locations of lows, highs, fronts, precipitation (including type) and cloud cover, (6) Hourly plots of icing pilot reports, providing the icing intensity, icing type, icing altitudes and aircraft type, (7) Hourly, regional radar mosaics, providing fine resolution of the locations of precipitation (including intensity and type), pilot reports of icing (including intensity and type), surface observations of precipitation type and Twin Otter tracks for a one hour window centered on the time of the radar data, and (8) Plots of data from individual NEXRAD radars at times and elevation angles that have been matched to Twin Otter flight locations. Outages occurred in nearly every dataset at some point. All relevant data that was available is presented here. All times are in UTC and all heights are in feet above mean sea level (MSL).

[Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

PubMed

Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

2015-05-01

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.

Classification of Arctic, Mid-Latitude and Tropical Clouds in the Mixed-Phase Temperature Regime

NASA Astrophysics Data System (ADS)

Costa, Anja; Afchine, Armin; Luebke, Anna; Meyer, Jessica; Dorsey, James R.; Gallagher, Martin W.; Ehrlich, André; Wendisch, Manfred; Krämer, Martina

2016-04-01

The degree of glaciation and the sizes and habits of ice particles formed in mixed-phase clouds remain not fully understood. However, these properties define the mixed clouds' radiative impact on the Earth's climate and thus a correct representation of this cloud type in global climate models is of importance for an improved certainty of climate predictions. This study focuses on the occurrence and characteristics of two types of clouds in the mixed-phase temperature regime (238-275K): coexistence clouds (Coex), in which both liquid drops and ice crystals exist, and fully glaciated clouds that develop in the Wegener-Bergeron-Findeisen regime (WBF clouds). We present an extensive dataset obtained by the Cloud and Aerosol Particle Spectrometer NIXE-CAPS, covering Arctic, mid-latitude and tropical regions. In total, we spent 45.2 hours within clouds in the mixed-phase temperature regime during five field campaigns (Arctic: VERDI, 2012 and RACEPAC, 2014 - Northern Canada; mid-latitude: COALESC, 2011 - UK and ML-Cirrus, 2014 - central Europe; tropics: ACRIDICON, 2014 - Brazil). We show that WBF and Coex clouds can be identified via cloud particle size distributions. The classified datasets are used to analyse temperature dependences of both cloud types as well as range and frequencies of cloud particle concentrations and sizes. One result is that Coex clouds containing supercooled liquid drops are found down to temperatures of -40 deg C only in tropical mixed clouds, while in the Arctic and mid-latitudes no liquid drops are observed below about -20 deg C. In addition, we show that the cloud particles' aspherical fractions - derived from polarization signatures of particles with diameters between 20 and 50 micrometers - differ significantly between WBF and Coex clouds. In Coex clouds, the aspherical fraction of cloud particles is generally very low, but increases with decreasing temperature. In WBF clouds, where all cloud particles are ice, about 20-40% of the cloud particles are nevertheless classified as spherical for all temperatures, possibly indicating columnar ice crystals (see Järvinen et al, submitted to JAS 2016).

Processing Uav and LIDAR Point Clouds in Grass GIS

NASA Astrophysics Data System (ADS)

Petras, V.; Petrasova, A.; Jeziorska, J.; Mitasova, H.

2016-06-01

Today's methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV) imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM), and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM). Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL), Point Cloud Library (PCL), and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.

Modeling the Effects of Inhomogeneous Aerosols on the Hot Jupiter Kepler-7b’s Atmospheric Circulation

NASA Astrophysics Data System (ADS)

Roman, Michael; Rauscher, Emily

2017-11-01

Motivated by observational evidence of inhomogeneous clouds in exoplanetary atmospheres, we investigate how proposed simple cloud distributions can affect atmospheric circulations and infrared emission. We simulated temperatures and winds for the hot Jupiter Kepler-7b using a three-dimensional atmospheric circulation model that included a simplified aerosol radiative transfer model. We prescribed fixed cloud distributions and scattering properties based on results previously inferred from Kepler-7b optical phase curves, including inhomogeneous aerosols centered along the western terminator and hypothetical cases in which aerosols additionally extended across much of the planet’s nightside. In all cases, a strong jet capable of advecting aerosols from a cooler nightside to dayside was found to persist, but only at the equator. Colder temperatures at mid and polar latitudes might permit aerosol to form on the dayside without the need for advection. By altering the deposition and redistribution of heat, aerosols along the western terminator produced an asymmetric heating that effectively shifts the hottest spot further east of the substellar point than expected for a uniform distribution. The addition of opaque high clouds on the nightside can partly mitigate this enhanced shift by retaining heat that contributes to warming west of the hotspot. These expected differences in infrared phase curves could place constraints on proposed cloud distributions and their infrared opacities for brighter hot Jupiters.

Analysis of a jet stream induced gravity wave associated with an observed ice cloud over Greenland

NASA Astrophysics Data System (ADS)

Buss, S.; Hertzog, A.; Hostettler, C.; Bui, T. P.; Lüthi, T.; Wernli, H.

2003-11-01

A polar stratospheric ice cloud (PSC type II) was observed by airborne lidar above Greenland on 14 January 2000. Is was the unique observation of an ice cloud over Greenland during the SOLVE/THESEO 2000 campaign. Mesoscale simulations with the hydrostatic HRM model are presented which, in contrast to global analyses, are capable to produce a vertically propagating gravity wave that induces the low temperatures at the level of the PSC afforded for the ice formation. The simulated minimum temperature is ~8 K below the driving analyses and ~3 K below the frost point, exactly coinciding with the location of the observed ice cloud. Despite the high elevations of the Greenland orography the simulated gravity wave is not a mountain wave. Analyses of the horizontal wind divergence, of the background wind profiles, of backward gravity wave ray-tracing trajectories, of HRM experiments with reduced Greenland topography and of several instability diagnostics near the tropopause level provide consistent evidence that the wave is emitted by the geostrophic adjustment of a jet instability associated with an intense, rapidly evolving, anticyclonically curved jet stream. In order to evaluate the potential frequency of such non-orographic polar stratospheric cloud events, an approximate jet instability diagnostic is performed for the winter 1999/2000. It indicates that ice-PSCs are only occasionally generated by gravity waves emanating from an unstable jet.

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Combining the 3D model generated from point clouds and thermography to identify the defects presented on the facades of a building

NASA Astrophysics Data System (ADS)

Huang, Yishuo; Chiang, Chih-Hung; Hsu, Keng-Tsang

2018-03-01

Defects presented on the facades of a building do have profound impacts on extending the life cycle of the building. How to identify the defects is a crucial issue; destructive and non-destructive methods are usually employed to identify the defects presented on a building. Destructive methods always cause the permanent damages for the examined objects; on the other hand, non-destructive testing (NDT) methods have been widely applied to detect those defects presented on exterior layers of a building. However, NDT methods cannot provide efficient and reliable information for identifying the defects because of the huge examination areas. Infrared thermography is often applied to quantitative energy performance measurements for building envelopes. Defects on the exterior layer of buildings may be caused by several factors: ventilation losses, conduction losses, thermal bridging, defective services, moisture condensation, moisture ingress, and structure defects. Analyzing the collected thermal images can be quite difficult when the spatial variations of surface temperature are small. In this paper the authors employ image segmentation to cluster those pixels with similar surface temperatures such that the processed thermal images can be composed of limited groups. The surface temperature distribution in each segmented group is homogenous. In doing so, the regional boundaries of the segmented regions can be identified and extracted. A terrestrial laser scanner (TLS) is widely used to collect the point clouds of a building, and those point clouds are applied to reconstruct the 3D model of the building. A mapping model is constructed such that the segmented thermal images can be projected onto the 2D image of the specified 3D building. In this paper, the administrative building in Chaoyang University campus is used as an example. The experimental results not only provide the defect information but also offer their corresponding spatial locations in the 3D model.

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.

Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

NASA Astrophysics Data System (ADS)

Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

2018-04-01

In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

NASA Technical Reports Server (NTRS)

Hodges, D. B.

1976-01-01

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

The One to Multiple Automatic High Accuracy Registration of Terrestrial LIDAR and Optical Images

NASA Astrophysics Data System (ADS)

Wang, Y.; Hu, C.; Xia, G.; Xue, H.

2018-04-01

The registration of ground laser point cloud and close-range image is the key content of high-precision 3D reconstruction of cultural relic object. In view of the requirement of high texture resolution in the field of cultural relic at present, The registration of point cloud and image data in object reconstruction will result in the problem of point cloud to multiple images. In the current commercial software, the two pairs of registration of the two kinds of data are realized by manually dividing point cloud data, manual matching point cloud and image data, manually selecting a two - dimensional point of the same name of the image and the point cloud, and the process not only greatly reduces the working efficiency, but also affects the precision of the registration of the two, and causes the problem of the color point cloud texture joint. In order to solve the above problems, this paper takes the whole object image as the intermediate data, and uses the matching technology to realize the automatic one-to-one correspondence between the point cloud and multiple images. The matching of point cloud center projection reflection intensity image and optical image is applied to realize the automatic matching of the same name feature points, and the Rodrigo matrix spatial similarity transformation model and weight selection iteration are used to realize the automatic registration of the two kinds of data with high accuracy. This method is expected to serve for the high precision and high efficiency automatic 3D reconstruction of cultural relic objects, which has certain scientific research value and practical significance.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

A CERES-like Cloud Property Climatology Using AVHRR Data

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Physical chemistry of the H2SO4/HNO3/H2O system - Implications for polar stratospheric clouds

NASA Technical Reports Server (NTRS)

Molina, M. J.; Zhang, R.; Wooldridge, P. J.; Mcmahon, J. R.; Kim, J. E.; Chang, H. Y.; Beyer, K. D.

1993-01-01

Polar stratospheric clouds (PSCs) play a key role in stratospheric ozone depletion. Surface-catalyzed reactions on PSC particles generate chlorine compounds that photolyze readily to yield chlorine radicals, which in turn destroy ozone very efficiently. The most prevalent PSCs form at temperatures several degrees above the ice frost point and are believed to consist of HNO3 hydrates; however, their formation mechanism is unclear. Results of laboratory experiments are presented which indicate that the background stratospheric H2SO4/H2O aerosols provide an essential link in this mechanism: These liquid aerosols absorb significant amounts of HNO3 vapor, leading most likely to the crystallization of nitric acid trihydrate (NAT). The frozen particles then grow to form PSCs by condensation of additional amounts of HNO3 and H2O vapor. Furthermore, reaction probability measurements reveal that the chlorine radical precursors are formed readily at polar stratospheric temperatures not just on NAT and ice crystals, but also on liquid H2SO4 solutions and on solid H2SO4 hydrates. These results imply that the chlorine activation efficiency of the aerosol particles increases rapidly as the temperature approaches the ice frost point regardless of the phase or composition of the particles.

Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds

NASA Astrophysics Data System (ADS)

Boerner, R.; Kröhnert, M.

2016-06-01

3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.

An Approach of Web-based Point Cloud Visualization without Plug-in

NASA Astrophysics Data System (ADS)

Ye, Mengxuan; Wei, Shuangfeng; Zhang, Dongmei

2016-11-01

With the advances in three-dimensional laser scanning technology, the demand for visualization of massive point cloud is increasingly urgent, but a few years ago point cloud visualization was limited to desktop-based solutions until the introduction of WebGL, several web renderers are available. This paper addressed the current issues in web-based point cloud visualization, and proposed a method of web-based point cloud visualization without plug-in. The method combines ASP.NET and WebGL technologies, using the spatial database PostgreSQL to store data and the open web technologies HTML5 and CSS3 to implement the user interface, a visualization system online for 3D point cloud is developed by Javascript with the web interactions. Finally, the method is applied to the real case. Experiment proves that the new model is of great practical value which avoids the shortcoming of the existing WebGIS solutions.

Model for Semantically Rich Point Cloud Data

NASA Astrophysics Data System (ADS)

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

2017-10-01

This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

Self-Similar Spin Images for Point Cloud Matching

NASA Astrophysics Data System (ADS)

Pulido, Daniel

The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Radiative consequences of low-temperature infrared refractive indices for supercooled water clouds

NASA Astrophysics Data System (ADS)

Rowe, P. M.; Neshyba, S.; Walden, V. P.

2013-07-01

Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water. Although conventional algorithms employ a temperature independent assumption (TIA), recent infrared measurements of supercooled water have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. Here, we assess biases that result from ignoring this temperature dependence. We show that TIA-based cloud retrievals introduce spurious ice into pure, supercooled clouds, or underestimate cloud thickness and droplet size. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W m-2 (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W m-2 (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted. The current experimental uncertainty in the CRI at low temperatures must be reduced to properly account for supercooled clouds in both climate models and cloud property retrievals.

Radiative consequences of low-temperature infrared refractive indices for supercooled water clouds

NASA Astrophysics Data System (ADS)

Rowe, P. M.; Neshyba, S.; Walden, V. P.

2013-12-01

Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water. Although conventional algorithms employ a temperature-independent assumption (TIA), recent infrared measurements of supercooled water have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. Here, we assess biases that result from ignoring this temperature dependence. We show that TIA-based cloud retrievals introduce spurious ice into pure, supercooled clouds, or underestimate cloud optical thickness and droplet size. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W m-2 (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W m-2 (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted. The current experimental uncertainty in the CRI at low temperatures must be reduced to account for supercooled clouds properly in both climate models and cloud-property retrievals.

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

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

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

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

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

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

a Fast Method for Measuring the Similarity Between 3d Model and 3d Point Cloud

NASA Astrophysics Data System (ADS)

Zhang, Zongliang; Li, Jonathan; Li, Xin; Lin, Yangbin; Zhang, Shanxin; Wang, Cheng

2016-06-01

This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.

Insights on TTL Dehydration Mechanisms from Microphysical Modelling of Aircraft Observations

NASA Technical Reports Server (NTRS)

Ueyama, R.; Pfister, L.; Jensen, E.

2014-01-01

The Tropical Tropopause Layer (TTL), a transition layer between the upper troposphere and lower stratosphere in the tropics, serves as the entryway of various trace gases into the stratosphere. Of particular interest is the transport of water vapor through the TTL, as WV is an important greenhouse gas and also plays a significant role in stratospheric chemistry by affecting polar stratospheric cloud formation and the ozone budget. While the dominant control of stratospheric water vapor by tropical cold point temperatures via the "freeze-drying" process is generally well understood, the details of the TTL dehydration mechanisms, including the relative roles of deep convection, atmospheric waves and cloud microphysical processes, remain an active area of research. The dynamical and microphysical processes that influence TTL water vapor concentrations are investigated in simulations of cloud formation and dehydration along air parcel trajectories. We first confirm the validity of our Lagrangian models in a case study involving measurements from the Airborne Tropical TRopopause EXperiment (ATTREX) flights over the central and eastern tropical Pacific in Oct-Nov 2011 and Jan-Feb 2013. ERA-Interim winds and seasonal mean heating rates from Yang et al. (2010) are used to advance parcels back in time from the flight tracks, and time-varying vertical profiles of water vapor along the diabatic trajectories are calculated in a one-dimensional cloud model as in Jensen and Pfister (2004) but with more reliable temperature field, wave and convection schemes. The simulated water vapor profiles demonstrate a significant improvement over estimates based on the Lagrangian Dry Point, agreeing well with aircraft observations when the effects of cloud microphysics, subgrid-scale gravity waves and convection are included. Following this approach, we examine the dynamical and microphysical control of TTL water vapor in the 30ºS-30ºN latitudinal belt and elucidate the dominant processes in the winter and summer seasons. Implications of the TTL dehydration processes for the regulation of global stratospheric humidity will be discussed.

How Cool was the Eclipse? Atmospheric Measurements and Citizen Science via NASA's GLOBE Observer

NASA Astrophysics Data System (ADS)

Weaver, K. L. K.; Riebeek Kohl, H.

2017-12-01

The solar eclipse of 2017 presented an extraordinary opportunity to engage the public in shared science activity across the entire United States. While a natural focus of the eclipse was on astronomy and heliophysics, there was also an opening for excellent connections to Earth science. Because of the excitement of the event, many people gathered for long periods before and after totality, a perfect opportunity for observations and data collection to explore the impact of the eclipse on the atmosphere. The data was collected via NASA's GLOBE Observer app, a subset of the Global Learning and Observations to Benefit the Environment Program, a citizen science project which has been active for more than 20 years training teachers to collect many different types of environmental science data with their students. GLOBE Observer expands that audience to citizen scientists who might not be connected to a school, but are still interested in collecting data. In addition to the clouds observations that are normally part of GLOBE Observer, a special temporary protocol was added for the eclipse to include air temperature. Both types of measurements were collected at regular intervals for several hours before and after the point of maximum eclipse. By crowdsourcing data from all across the United States, on and off the path of totality, the hope was to be able to see patterns that wouldn't be apparent with fewer data points. In particular, there are few sources of detailed cloud data from the ground, including cloud type as well as overall cloud cover, especially as collected during a unique natural experiment such as an eclipse. This presentation will report preliminary results of the GLOBE Observer eclipse citizen science project, including participation totals and impact, data site distribution, as well as early analyses of both temperature and cloud data.

Motion Estimation System Utilizing Point Cloud Registration

NASA Technical Reports Server (NTRS)

Chen, Qi (Inventor)

2016-01-01

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

Pointo - a Low Cost Solution to Point Cloud Processing

NASA Astrophysics Data System (ADS)

Houshiar, H.; Winkler, S.

2017-11-01

With advance in technology access to data especially 3D point cloud data becomes more and more an everyday task. 3D point clouds are usually captured with very expensive tools such as 3D laser scanners or very time consuming methods such as photogrammetry. Most of the available softwares for 3D point cloud processing are designed for experts and specialists in this field and are usually very large software packages containing variety of methods and tools. This results in softwares that are usually very expensive to acquire and also very difficult to use. Difficulty of use is caused by complicated user interfaces that is required to accommodate a large list of features. The aim of these complex softwares is to provide a powerful tool for a specific group of specialist. However they are not necessary required by the majority of the up coming average users of point clouds. In addition to complexity and high costs of these softwares they generally rely on expensive and modern hardware and only compatible with one specific operating system. Many point cloud customers are not point cloud processing experts or willing to spend the high acquisition costs of these expensive softwares and hardwares. In this paper we introduce a solution for low cost point cloud processing. Our approach is designed to accommodate the needs of the average point cloud user. To reduce the cost and complexity of software our approach focuses on one functionality at a time in contrast with most available softwares and tools that aim to solve as many problems as possible at the same time. Our simple and user oriented design improve the user experience and empower us to optimize our methods for creation of an efficient software. In this paper we introduce Pointo family as a series of connected softwares to provide easy to use tools with simple design for different point cloud processing requirements. PointoVIEWER and PointoCAD are introduced as the first components of the Pointo family to provide a fast and efficient visualization with the ability to add annotation and documentation to the point clouds.

Cloud Point Extraction for Electroanalysis: Anodic Stripping Voltammetry of Cadmium.

PubMed

Rusinek, Cory A; Bange, Adam; Papautsky, Ian; Heineman, William R

2015-06-16

Cloud point extraction (CPE) is a well-established technique for the preconcentration of hydrophobic species from water without the use of organic solvents. Subsequent analysis is then typically performed via atomic absorption spectroscopy (AAS), UV-vis spectroscopy, or high performance liquid chromatography (HPLC). However, the suitability of CPE for electroanalytical methods such as stripping voltammetry has not been reported. We demonstrate the use of CPE for electroanalysis using the determination of cadmium (Cd(2+)) by anodic stripping voltammetry (ASV). Rather than using the chelating agents which are commonly used in CPE to form a hydrophobic, extractable metal complex, we used iodide and sulfuric acid to neutralize the charge on Cd(2+) to form an extractable ion pair. This offers good selectivity for Cd(2+) as no interferences were observed from other heavy metal ions. Triton X-114 was chosen as the surfactant for the extraction because its cloud point temperature is near room temperature (22-25 °C). Bare glassy carbon (GC), bismuth-coated glassy carbon (Bi-GC), and mercury-coated glassy carbon (Hg-GC) electrodes were compared for the CPE-ASV. A detection limit for Cd(2+) of 1.7 nM (0.2 ppb) was obtained with the Hg-GC electrode. ASV with CPE gave a 20x decrease (4.0 ppb) in the detection limit compared to ASV without CPE. The suitability of this procedure for the analysis of tap and river water samples was demonstrated. This simple, versatile, environmentally friendly, and cost-effective extraction method is potentially applicable to a wide variety of transition metals and organic compounds that are amenable to detection by electroanalytical methods.

Six Martian years of CO2 clouds survey by OMEGA/MEx.

NASA Astrophysics Data System (ADS)

Gondet, Brigitte; bibring, Jean-Pierre; Vincendon, Mathieu

2014-05-01

Mesospheric clouds have been detected first from Earth (Bell et al 1996 [1]), then from Mars orbit (MGS/TES and MOC, Clancy et al 1998 [2]). Their composition (CO2) was inferred from temperature. Similar detection and temperature-inferred composition was then performed by Spicam and PFS on board Mars Express (Monmessin et al [3], Formisano et al [4]., 2006). The first direct detection and characterization (altitude, composition, velocity) was performed by OMEGA/ Mars Express (then coupled to HRSC/ Mars Express, and confirmed by CRISM/MRO (Montmessin et al. [5], 2007, Maattanen et al [6]., Scholten et al. [7], 2010, Vincendon et al [8]., 2011). Omega is a very powerful tool for the study of CO2 clouds as it is able to unambiguously identify the CO2 composition of a cloud based on a near-IR spectral feature located at 4.26 μm [5],. Therefore since the beginning of the Mars Express mission (2004) OMEGA as done a systematic survey of these mesospheric clouds. Thanks to the orbit of Mars Express, we can observe this clouds from different altitudes (from apocenter to pericenter) and at different local times. We will present the result of 6 Martians years of observations and point out a correlation with the dust activity. We also observe that their time of appearance/disappearance varies slightly from year to year. We will mention also the existence of mesospheric H2O clouds. References [1] JF Bell. et al. JGR 1996; [2] RT Clancy et al., GRL 1998 [3] F. Montmessin et al. JGR 2006; [4] V. Formisano et al., Icarus 2006; [5] F. Montmessin et al JGR 2007 [6] A. Määttänen et al. Icarus 2010; [7] F. Scholten et al. PSS 2010; [8] M. Viencendon et al. JGR 2011

Mesospheric CO2 Clouds at Mars: Seven Martian Years Survey by OMEGA/MEX

NASA Astrophysics Data System (ADS)

Gondet, Brigitte; Bibring, Jean-Pierre

2016-04-01

Mesospheric clouds have been detected first from Earth (Bell et al 1996 [1]), then from Mars orbit (MGS/TES and MOC, Clancy et al 1998 [2]). Their composition (CO2) was inferred from temperature. Similar detection and temperature-inferred composition was then performed by Spicam and PFS on board Mars Express (Monmessin et al [3], Formisano et al [4]. 2006). The first direct detection and characterization (altitude, composition, velocity) was performed by OMEGA/ Mars Express (then coupled to HRSC/ Mars Express, and confirmed by CRISM/MRO (Montmessin et al. [5], 2007, Maattanen et al [6]. Scholten et al. [7], 2010, Vincendon et al [8], 2011). Omega is a very powerful tool for the study of CO2 clouds as it is able to unambiguously identify the CO2 composition of a cloud based on a near-IR spectral feature located at 4.26 μm [5] Therefore since the beginning of the Mars Express mission (2004) OMEGA as done a systematic survey of these mesospheric clouds. Thanks to the orbit of Mars Express, we can observe this clouds from different altitudes (from apocenter to pericenter) and at different local times. We will present the result of 7 Martians years of observations, point out a correlation with the dust activity and an irregular concentration of clouds from years to years. References [1] JF Bell. et al. JGR 1996; [2] RT Clancy et al., GRL 1998 [3] F. Montmessin et al. JGR 2006; [4] V. Formisano et al., Icarus 2006; [5] F. Montmessin et al JGR 2007 [6] A. Määttänen et al. Icarus 2010; [7] F. Scholten et al. PSS 2010; [8] M. Viencendon et al. JGR 2011

THE YOUNG STELLAR OBJECT POPULATION IN THE VELA-D MOLECULAR CLOUD

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

Strafella, F.; Maruccia, Y.; Maiolo, B.

2015-01-10

We investigate the young stellar population in the Vela Molecular Ridge, Cloud-D, a star-forming region observed by both the Spitzer/NASA and Herschel/ESA space telescopes. The point-source, band-merged, Spitzer-IRAC catalog complemented with MIPS photometry previously obtained is used to search for candidate young stellar objects (YSOs), also including sources detected in less than four IRAC bands. Bona fide YSOs are selected by using appropriate color-color and color-magnitude criteria aimed at excluding both Galactic and extragalactic contaminants. The derived star formation rate and efficiency are compared with the same quantities characterizing other star-forming clouds. Additional photometric data, spanning from the near-IR tomore » the submillimeter, are used to evaluate both bolometric luminosity and temperature for 33 YSOs located in a region of the cloud observed by both Spitzer and Herschel. The luminosity-temperature diagram suggests that some of these sources are representative of Class 0 objects with bolometric temperatures below 70 K and luminosities of the order of the solar luminosity. Far-IR observations from the Herschel/Hi-GAL key project for a survey of the Galactic plane are also used to obtain a band-merged photometric catalog of Herschel sources intended to independently search for protostars. We find 122 Herschel cores located on the molecular cloud, 30 of which are protostellar and 92 of which are starless. The global protostellar luminosity function is obtained by merging the Spitzer and Herschel protostars. Considering that 10 protostars are found in both the Spitzer and Herschel lists, it follows that in the investigated region we find 53 protostars and that the Spitzer-selected protostars account for approximately two-thirds of the total.« less

Study of Huizhou architecture component point cloud in surface reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Runmei; Wang, Guangyin; Ma, Jixiang; Wu, Yulu; Zhang, Guangbin

2017-06-01

Surface reconfiguration softwares have many problems such as complicated operation on point cloud data, too many interaction definitions, and too stringent requirements for inputing data. Thus, it has not been widely popularized so far. This paper selects the unique Huizhou Architecture chuandou wooden beam framework as the research object, and presents a complete set of implementation in data acquisition from point, point cloud preprocessing and finally implemented surface reconstruction. Firstly, preprocessing the acquired point cloud data, including segmentation and filtering. Secondly, the surface’s normals are deduced directly from the point cloud dataset. Finally, the surface reconstruction is studied by using Greedy Projection Triangulation Algorithm. Comparing the reconstructed model with the three-dimensional surface reconstruction softwares, the results show that the proposed scheme is more smooth, time efficient and portable.

Balloon borne Antarctic frost point measurements and their impact on polar stratospheric cloud theories

NASA Technical Reports Server (NTRS)

Rosen, James M.; Hofmann, D. J.; Carpenter, J. R.; Harder, J. W.; Oltsmans, S. J.

1988-01-01

Balloon-borne frost point measurements were performed over Antarctica during September-October 1987 as part of the NOZE II effort at McMurdo. The results show water mixing ratios on the order of 2 ppmv in the 20 km region, suggesting that models of the springtime Antarctic stratosphere should be based on approximately 2 ppmv water vapor. Evidence indicating that some PSCs form at temperatures higher than the frost point in the 15 to 20 km region is discussed. This supports the binary HNO3-H2O theory of PSC composition.

The Continuation of Cloud Statistics for NASA Climate Change Studies

NASA Technical Reports Server (NTRS)

Wylie, Donald P.

2001-01-01

The weather systems, cyclones, and anticyclones, along with air trajectories and cloud forms, are compared to past studies of the Arctic to assess compatibility of the four month study of the Arctic Cloud Experiment flights of the First ISCCP Regional Experiment (FIRE/ACE) with past climatologies. The frequency and movement of cyclones (lows) and anticyclones (highs) followed the general eastward and northeastward directions indicated by past studies. Most cyclones (lows) came from eastern Siberia and the Bering Sea to the south and moved north across the Bering Straight or Alaska into the Arctic Ocean. They generally weakened in central pressure as they moved poleward. Anticyclones (highs) were most common in the eastern Beaufort Sea near Canada in June and July as predicted from previous studies. However, many cyclones and anticyclones moved in westward directions which is rare in other latitudes. Erratic changes in shape and intensity on a daily basis also were observed. The National Center for Environmental Prediction (NCEP) analysis generally reflected the Surface Heat Budget in the Arctic (SHEBA) Ship World Meteorological Organization (WMO) observations which it used. However, NCEP temperatures were biased warm by 1.0 to 1.5 C in April and early May. In July when the surface temperature were at the freezing/thawing point, the NCEP analysis changed to a cold bias of -1.0 C. Dew points had smaller biases except for July where they were biased cold by -1.4 C. Wind speeds had a -2 m/s low bias for the six windiest days. Surface barometric pressures had consistently low biases from -1.2 to -2.8 hPa in all four months. Air parcel historical trajectories were mainly from the south or from local anticyclonic gyres in the Beaufort Sea. Most air came to the SHEBA Ship from the north Pacific Ocean or from Alaska and Canada and occasionally from eastern Siberia. Very few trajectories traced back across the pole to Europe and Central Asia. Cloud cover was high, as expected, from 69-86% of the time. Satellite data also indicate frequent stratus, altostratus, and cirrus clouds (occurring 61% of the time) above the expected boundary layer fog and Arctic stratus clouds.

What's the Point of a Raster ? Advantages of 3D Point Cloud Processing over Raster Based Methods for Accurate Geomorphic Analysis of High Resolution Topography.

NASA Astrophysics Data System (ADS)

Lague, D.

2014-12-01

High Resolution Topographic (HRT) datasets are predominantly stored and analyzed as 2D raster grids of elevations (i.e., Digital Elevation Models). Raster grid processing is common in GIS software and benefits from a large library of fast algorithms dedicated to geometrical analysis, drainage network computation and topographic change measurement. Yet, all instruments or methods currently generating HRT datasets (e.g., ALS, TLS, SFM, stereo satellite imagery) output natively 3D unstructured point clouds that are (i) non-regularly sampled, (ii) incomplete (e.g., submerged parts of river channels are rarely measured), and (iii) include 3D elements (e.g., vegetation, vertical features such as river banks or cliffs) that cannot be accurately described in a DEM. Interpolating the raw point cloud onto a 2D grid generally results in a loss of position accuracy, spatial resolution and in more or less controlled interpolation. Here I demonstrate how studying earth surface topography and processes directly on native 3D point cloud datasets offers several advantages over raster based methods: point cloud methods preserve the accuracy of the original data, can better handle the evaluation of uncertainty associated to topographic change measurements and are more suitable to study vegetation characteristics and steep features of the landscape. In this presentation, I will illustrate and compare Point Cloud based and Raster based workflows with various examples involving ALS, TLS and SFM for the analysis of bank erosion processes in bedrock and alluvial rivers, rockfall statistics (including rockfall volume estimate directly from point clouds) and the interaction of vegetation/hydraulics and sedimentation in salt marshes. These workflows use 2 recently published algorithms for point cloud classification (CANUPO) and point cloud comparison (M3C2) now implemented in the open source software CloudCompare.

Particle backscatter and relative humidity measured across cirrus clouds and comparison with microphysical cirrus modelling

NASA Astrophysics Data System (ADS)

Brabec, M.; Wienhold, F. G.; Luo, B. P.; Vömel, H.; Immler, F.; Steiner, P.; Hausammann, E.; Weers, U.; Peter, T.

2012-10-01

Advanced measurement and modelling techniques are employed to estimate the partitioning of atmospheric water between the gas phase and the condensed phase in and around cirrus clouds, and thus to identify in-cloud and out-of-cloud supersaturations with respect to ice. In November 2008 the newly developed balloon-borne backscatter sonde COBALD (Compact Optical Backscatter and AerosoL Detector) was flown 14 times together with a CFH (Cryogenic Frost point Hygrometer) from Lindenberg, Germany (52° N, 14° E). The case discussed here in detail shows two cirrus layers with in-cloud relative humidities with respect to ice between 50% and 130%. Global operational analysis data of ECMWF (roughly 1° × 1° horizontal and 1 km vertical resolution, 6-hourly stored fields) fail to represent ice water contents and relative humidities. Conversely, regional COSMO-7 forecasts (6.6 km × 6.6 km, 5-min stored fields) capture the measured humidities and cloud positions remarkably well. The main difference between ECMWF and COSMO data is the resolution of small-scale vertical features responsible for cirrus formation. Nevertheless, ice water contents in COSMO-7 are still off by factors 2-10, likely reflecting limitations in COSMO's ice phase bulk scheme. Significant improvements can be achieved by comprehensive size-resolved microphysical and optical modelling along backward trajectories based on COSMO-7 wind and temperature fields, which allow accurate computation of humidities, homogeneous ice nucleation, resulting ice particle size distributions and backscatter ratios at the COBALD wavelengths. However, only by superimposing small-scale temperature fluctuations, which remain unresolved by the numerical weather prediction models, can we obtain a satisfying agreement with the observations and reconcile the measured in-cloud non-equilibrium humidities with conventional ice cloud microphysics. Conversely, the model-data comparison provides no evidence that additional changes to ice-cloud microphysics - such as heterogeneous nucleation or changing the water vapour accommodation coefficient on ice - are required.

Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform.

PubMed

De Queiroz, Ricardo; Chou, Philip A

2016-06-01

In free-viewpoint video, there is a recent trend to represent scene objects as solids rather than using multiple depth maps. Point clouds have been used in computer graphics for a long time and with the recent possibility of real time capturing and rendering, point clouds have been favored over meshes in order to save computation. Each point in the cloud is associated with its 3D position and its color. We devise a method to compress the colors in point clouds which is based on a hierarchical transform and arithmetic coding. The transform is a hierarchical sub-band transform that resembles an adaptive variation of a Haar wavelet. The arithmetic encoding of the coefficients assumes Laplace distributions, one per sub-band. The Laplace parameter for each distribution is transmitted to the decoder using a custom method. The geometry of the point cloud is encoded using the well-established octtree scanning. Results show that the proposed solution performs comparably to the current state-of-the-art, in many occasions outperforming it, while being much more computationally efficient. We believe this work represents the state-of-the-art in intra-frame compression of point clouds for real-time 3D video.

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

NASA Technical Reports Server (NTRS)

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

1996-01-01

Cirrus cloud radiative and physical characteristics are determined using a combination of ground based, aircraft, and satellite measurements taken as part of the First ISCCP Region Experiment (FIRE) cirrus intensive field observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center and top heights and the corresponding temperatures. Coincident GOES-4 4-km visible (0.65 micrometer) and 8-km infrared window (11.5 micrometer) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 062 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance , extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface-based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature wer ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperature and cloud thickness from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. the parameterization of visible reflectance in terms of cloud optical depth and clear sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous advanced very high resolution radiometer (AVHRR) data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloud pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study or cirrus cloud scattering processes and remote sensing techniques.

Characterization of the Cloud-Topped Boundary Layer at the Synoptic Scale Using AVHRR Observations during the SEMAPHORE Experiment.

NASA Astrophysics Data System (ADS)

Mathieu, A.; Sèze, G.; Lahellec, A.; Guerin, C.; Weill, A.

2003-12-01

Satellite platforms NOAA-11 and -12 Advanced Very High Resolution Radiometer (AVHRR) data are used during the daytime to study large sheets of stratocumulus over the North Atlantic Ocean. The application concerns an anticyclonic period of the Structure des Echanges Mer Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherché Expérimentale (SEMAPHORE) campaign (10 17 November 1993). In the region of interest, the satellite images are recorded under large solar zenith angles. Extending the SEMAPHORE area, a region of about 3000 × 3000 km2 is studied to characterize the atmospheric boundary layer. A statistical cloud classification method is applied to discriminate for low-level and optically thick clouds. For AVHRR pixels covered with thick clouds, brightness temperatures are used to evaluate the boundary layer cloud-top temperature (CTT). The objective is to obtain accurate CTT maps for evaluation of a global model. In this application, the full-resolution fields are reduced to match model grid size. An estimate of overall temperature uncertainty associated with each grid point is also derived, which incorporates subgrid variability of the fields and quality of the temperature retrieval. Results are compared with the SEMAPHORE campaign measurements. A comparison with “DX” products obtained with the same dataset, but at lower resolution, is also presented. The authors claim that such instantaneous CTT maps could be as intensively used as classical SST maps, and both could be efficiently complemented with gridpoint error-bar maps. They may be used for multiple applications: (i) to provide a means to improve numerical weather prediction and climatological reanalyses, (ii) to represent a boundary layer global characterization to analyze the synoptic situation of field experiments, and (iii) to allow validation and to test development of large-scale and mesoscale models.

Does The Earth Have an Adaptive Infrared Iris?

NASA Technical Reports Server (NTRS)

Lindzen, Richard S.; Chou, Ming-Dah; Hou, Arthur

2000-01-01

Observations and analyses of water vapor and clouds in the tropics over the past decade suggest a different approach to radiative climate feedbacks: namely, that high clouds and high free-tropospheric relative humidity are largely tied to each other, and that the main feedback consists in changing the relative areas of cloudy/moist regions vis a vis clear/dry regions in response to the surface temperature of the cloudy/moist regions - as opposed to altering the humidity in either of the regions. This is an intrinsically 2-dimensional (horizontal and vertical) effect which does not readily enter simple 1-dimensional (vertical) radiative-convective schemes which emphasize average humidity, etc. Preliminary analyses of cloud data for the eastern part of the Western Pacific from the Japanese GMS-5(Geostationary Meteorological Satellite), are supportive of this suggestion - pointing to a 15% reduction in cloudy/moist area for a 1C increase of the sea surface temperature as measured by the cloud-weighted SST (sea surface temperature). The implication of this result is examined using a simple 2-dimensional radiative-convective model. The calculations show that such a change in the tropics would lead to a strong negative feedback in the global climate, with a feedback factor of about -1.7, which, if correct, would easily dominate the positive water vapor feedback found in current models. This new feedback mechanism, in effect, constitutes an adaptive infrared iris that opens and closes in order to control the OLR (outgoing longwave radiation) in response to changes in surface temperature in a manner similar to the way in which an eye's iris opens and closes in response to changing light levels. The climate sensitivity resulting from this thermostatic mechanism is consistent with the independent determination by Lindzen and Giannitisis (1998). Preliminary attempts to replicate observations with GCMs (General Circulation Models) suggest that models lack such a negative cloud/moist areal feedback.

TH-AB-202-08: A Robust Real-Time Surface Reconstruction Method On Point Clouds Captured From a 3D Surface Photogrammetry System

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

Liu, W; Sawant, A; Ruan, D

2016-06-15

Purpose: Surface photogrammetry (e.g. VisionRT, C-Rad) provides a noninvasive way to obtain high-frequency measurement for patient motion monitoring in radiotherapy. This work aims to develop a real-time surface reconstruction method on the acquired point clouds, whose acquisitions are subject to noise and missing measurements. In contrast to existing surface reconstruction methods that are usually computationally expensive, the proposed method reconstructs continuous surfaces with comparable accuracy in real-time. Methods: The key idea in our method is to solve and propagate a sparse linear relationship from the point cloud (measurement) manifold to the surface (reconstruction) manifold, taking advantage of the similarity inmore » local geometric topology in both manifolds. With consistent point cloud acquisition, we propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, building the point correspondences by the iterative closest point (ICP) method. To accommodate changing noise levels and/or presence of inconsistent occlusions, we further propose a modified sparse regression (MSR) model to account for the large and sparse error built by ICP, with a Laplacian prior. We evaluated our method on both clinical acquired point clouds under consistent conditions and simulated point clouds with inconsistent occlusions. The reconstruction accuracy was evaluated w.r.t. root-mean-squared-error, by comparing the reconstructed surfaces against those from the variational reconstruction method. Results: On clinical point clouds, both the SR and MSR models achieved sub-millimeter accuracy, with mean reconstruction time reduced from 82.23 seconds to 0.52 seconds and 0.94 seconds, respectively. On simulated point cloud with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent performance despite the introduced occlusions. Conclusion: We have developed a real-time and robust surface reconstruction method on point clouds acquired by photogrammetry systems. It serves an important enabling step for real-time motion tracking in radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less

FPFH-based graph matching for 3D point cloud registration

NASA Astrophysics Data System (ADS)

Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua

2018-04-01

Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.

Spectral signatures of polar stratospheric clouds and sulfate aerosol

NASA Technical Reports Server (NTRS)

Massie, S. T.; Bailey, P. L.; Gille, J. C.; Lee, E. C.; Mergenthaler, J. L.; Roche, A. E.; Kumer, J. B.; Fishbein, E. F.; Waters, J. W.; Lahoz, W. A.

1994-01-01

Multiwavelength observations of Antarctic and midlatitude aerosol by the Cryogenic Limb Array Etalon Spectrometer (CLAES) experiment on the Upper Atmosphere Research Satellite (UARS) are used to demonstrate a technique that identifies the location of polar stratospheric clouds. The technique discussed uses the normalized area of the triangle formed by the aerosol extinctions at 925, 1257, and 1605/cm (10.8, 8.0, and 6.2 micrometers) to derive a spectral aerosol measure M of the aerosol spectrum. Mie calculations for spherical particles and T-matrix calculations for spheriodal particles are used to generate theoretical spectral extinction curves for sulfate and polar stratospheric cloud particles. The values of the spectral aerosol measure M for the sulfate and polar stratospheric cloud particles are shown to be different. Aerosol extinction data, corresponding to temperatures between 180 and 220 K at a pressure of 46 hPa (near 21-km altitude) for 18 August 1992, are used to demonstrate the technique. Thermodynamic calculations, based upon frost-point calculations and laboratory phase-equilibrium studies of nitric acid trihydrate, are used to predict the location of nitric acid trihydrate cloud particles.

Analysis of 2015 Winter In-Flight Icing Case Studies with Ground-Based Remote Sensing Systems Compared to In-Situ SLW Sondes

NASA Technical Reports Server (NTRS)

Serke, David J.; King, Michael Christopher; Hansen, Reid; Reehorst, Andrew L.

2016-01-01

National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) have developed an icing remote sensing technology that has demonstrated skill at detecting and classifying icing hazards in a vertical column above an instrumented ground station. This technology has recently been extended to provide volumetric coverage surrounding an airport. Building on the existing vertical pointing system, the new method for providing volumetric coverage utilizes a vertical pointing cloud radar, a multi-frequency microwave radiometer with azimuth and elevation pointing, and a NEXRAD radar. The new terminal area icing remote sensing system processes the data streams from these instruments to derive temperature, liquid water content, and cloud droplet size for each examined point in space. These data are then combined to ultimately provide icing hazard classification along defined approach paths into an airport. To date, statistical comparisons of the vertical profiling technology have been made to Pilot Reports and Icing Forecast Products. With the extension into relatively large area coverage and the output of microphysical properties in addition to icing severity, the use of these comparators is not appropriate and a more rigorous assessment is required. NASA conducted a field campaign during the early months of 2015 to develop a database to enable the assessment of the new terminal area icing remote sensing system and further refinement of terminal area icing weather information technologies in general. In addition to the ground-based remote sensors listed earlier, in-situ icing environment measurements by weather balloons were performed to produce a comprehensive comparison database. Balloon data gathered consisted of temperature, humidity, pressure, super-cooled liquid water content, and 3-D position with time. Comparison data plots of weather balloon and remote measurements, weather balloon flight paths, bulk comparisons of integrated liquid water content and icing cloud extent agreement, and terminal-area hazard displays are presented. Discussions of agreement quality and paths for future development are also included.

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

NASA Technical Reports Server (NTRS)

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

1990-01-01

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the FIRE Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4-km visible (0.65 micro-m) and 8-km infrared window (11.5 micro-m) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 0.62 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance, extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface- based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature were ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperatures and cloud thicknesses from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. The parameterization of visible reflectance in terms of cloud optical depth and clear-sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous AVHRR data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloudy pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study of cirrus cloud scattering processes and remote sensing techniques.

Cloud-In-Cell modeling of shocked particle-laden flows at a ``SPARSE'' cost

NASA Astrophysics Data System (ADS)

Taverniers, Soren; Jacobs, Gustaaf; Sen, Oishik; Udaykumar, H. S.

2017-11-01

A common tool for enabling process-scale simulations of shocked particle-laden flows is Eulerian-Lagrangian Particle-Source-In-Cell (PSIC) modeling where each particle is traced in its Lagrangian frame and treated as a mathematical point. Its dynamics are governed by Stokes drag corrected for high Reynolds and Mach numbers. The computational burden is often reduced further through a ``Cloud-In-Cell'' (CIC) approach which amalgamates groups of physical particles into computational ``macro-particles''. CIC does not account for subgrid particle fluctuations, leading to erroneous predictions of cloud dynamics. A Subgrid Particle-Averaged Reynolds-Stress Equivalent (SPARSE) model is proposed that incorporates subgrid interphase velocity and temperature perturbations. A bivariate Gaussian source distribution, whose covariance captures the cloud's deformation to first order, accounts for the particles' momentum and energy influence on the carrier gas. SPARSE is validated by conducting tests on the interaction of a particle cloud with the accelerated flow behind a shock. The cloud's average dynamics and its deformation over time predicted with SPARSE converge to their counterparts computed with reference PSIC models as the number of Gaussians is increased from 1 to 16. This work was supported by AFOSR Grant No. FA9550-16-1-0008.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

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

2016-10-01

Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure.

Motion-Compensated Compression of Dynamic Voxelized Point Clouds.

PubMed

De Queiroz, Ricardo L; Chou, Philip A

2017-05-24

Dynamic point clouds are a potential new frontier in visual communication systems. A few articles have addressed the compression of point clouds, but very few references exist on exploring temporal redundancies. This paper presents a novel motion-compensated approach to encoding dynamic voxelized point clouds at low bit rates. A simple coder breaks the voxelized point cloud at each frame into blocks of voxels. Each block is either encoded in intra-frame mode or is replaced by a motion-compensated version of a block in the previous frame. The decision is optimized in a rate-distortion sense. In this way, both the geometry and the color are encoded with distortion, allowing for reduced bit-rates. In-loop filtering is employed to minimize compression artifacts caused by distortion in the geometry information. Simulations reveal that this simple motion compensated coder can efficiently extend the compression range of dynamic voxelized point clouds to rates below what intra-frame coding alone can accommodate, trading rate for geometry accuracy.

A portable low-cost 3D point cloud acquiring method based on structure light

NASA Astrophysics Data System (ADS)

Gui, Li; Zheng, Shunyi; Huang, Xia; Zhao, Like; Ma, Hao; Ge, Chao; Tang, Qiuxia

2018-03-01

A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.

Joint classification and contour extraction of large 3D point clouds

NASA Astrophysics Data System (ADS)

Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

2017-08-01

We present an effective and efficient method for point-wise semantic classification and extraction of object contours of large-scale 3D point clouds. What makes point cloud interpretation challenging is the sheer size of several millions of points per scan and the non-grid, sparse, and uneven distribution of points. Standard image processing tools like texture filters, for example, cannot handle such data efficiently, which calls for dedicated point cloud labeling methods. It turns out that one of the major drivers for efficient computation and handling of strong variations in point density, is a careful formulation of per-point neighborhoods at multiple scales. This allows, both, to define an expressive feature set and to extract topologically meaningful object contours. Semantic classification and contour extraction are interlaced problems. Point-wise semantic classification enables extracting a meaningful candidate set of contour points while contours help generating a rich feature representation that benefits point-wise classification. These methods are tailored to have fast run time and small memory footprint for processing large-scale, unstructured, and inhomogeneous point clouds, while still achieving high classification accuracy. We evaluate our methods on the semantic3d.net benchmark for terrestrial laser scans with >109 points.

Point clouds segmentation as base for as-built BIM creation

NASA Astrophysics Data System (ADS)

Macher, H.; Landes, T.; Grussenmeyer, P.

2015-08-01

In this paper, a three steps segmentation approach is proposed in order to create 3D models from point clouds acquired by TLS inside buildings. The three scales of segmentation are floors, rooms and planes composing the rooms. First, floor segmentation is performed based on analysis of point distribution along Z axis. Then, for each floor, room segmentation is achieved considering a slice of point cloud at ceiling level. Finally, planes are segmented for each room, and planes corresponding to ceilings and floors are identified. Results of each step are analysed and potential improvements are proposed. Based on segmented point clouds, the creation of as-built BIM is considered in a future work section. Not only the classification of planes into several categories is proposed, but the potential use of point clouds acquired outside buildings is also considered.

High-Precision Registration of Point Clouds Based on Sphere Feature Constraints.

PubMed

Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter

2016-12-30

Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.

High-Precision Registration of Point Clouds Based on Sphere Feature Constraints

PubMed Central

Huang, Junhui; Wang, Zhao; Gao, Jianmin; Huang, Youping; Towers, David Peter

2016-01-01

Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method. PMID:28042846

A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study

NASA Technical Reports Server (NTRS)

Wang, Chunpeng; Lou, Zhengzhao Johnny; Chen, Xiuhong; Zeng, Xiping; Tao, Wei-Kuo; Huang, Xianglei

2014-01-01

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-micrometers brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat 1 Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-micrometers band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model.Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-mm channel is located at optical depth; approximately 0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between 230 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-micrometers brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6-10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

Biotoxicity and bioavailability of hydrophobic organic compounds solubilized in nonionic surfactant micelle phase and cloud point system.

PubMed

Pan, Tao; Liu, Chunyan; Zeng, Xinying; Xin, Qiao; Xu, Meiying; Deng, Yangwu; Dong, Wei

2017-06-01

A recent work has shown that hydrophobic organic compounds solubilized in the micelle phase of some nonionic surfactants present substrate toxicity to microorganisms with increasing bioavailability. However, in cloud point systems, biotoxicity is prevented, because the compounds are solubilized into a coacervate phase, thereby leaving a fraction of compounds with cells in a dilute phase. This study extends the understanding of the relationship between substrate toxicity and bioavailability of hydrophobic organic compounds solubilized in nonionic surfactant micelle phase and cloud point system. Biotoxicity experiments were conducted with naphthalene and phenanthrene in the presence of mixed nonionic surfactants Brij30 and TMN-3, which formed a micelle phase or cloud point system at different concentrations. Saccharomyces cerevisiae, unable to degrade these compounds, was used for the biotoxicity experiments. Glucose in the cloud point system was consumed faster than in the nonionic surfactant micelle phase, indicating that the solubilized compounds had increased toxicity to cells in the nonionic surfactant micelle phase. The results were verified by subsequent biodegradation experiments. The compounds were degraded faster by PAH-degrading bacterium in the cloud point system than in the micelle phase. All these results showed that biotoxicity of the hydrophobic organic compounds increases with bioavailability in the surfactant micelle phase but remains at a low level in the cloud point system. These results provide a guideline for the application of cloud point systems as novel media for microbial transformation or biodegradation.

Observational constraints on Arctic boundary-layer clouds, surface moisture and sensible heat fluxes

NASA Astrophysics Data System (ADS)

Wu, D. L.; Boisvert, L.; Klaus, D.; Dethloff, K.; Ganeshan, M.

2016-12-01

The dry, cold environment and dynamic surface variations make the Arctic a unique but difficult region for observations, especially in the atmospheric boundary layer (ABL). Spaceborne platforms have been the key vantage point to capture basin-scale changes during the recent Arctic warming. Using the AIRS temperature, moisture and surface data, we found that the Arctic surface moisture flux (SMF) had increased by 7% during 2003-2013 (18 W/m2 equivalent in latent heat), mostly in spring and fall near the Arctic coastal seas where large sea ice reduction and sea surface temperature (SST) increase were observed. The increase in Arctic SMF correlated well with the increases in total atmospheric column water vapor and low-level clouds, when compared to CALIPSO cloud observations. It has been challenging for climate models to reliably determine Arctic cloud radiative forcing (CRF). Using the regional climate model HIRHAM5 and assuming a more efficient Bergeron-Findeisen process with generalized subgrid-scale variability for total water content, we were able to produce a cloud distribution that is more consistent with the CloudSat/CALIPSO observations. More importantly, the modified schemes decrease (increase) the cloud water (ice) content in mixed-phase clouds, which help to improve the modeled CRF and energy budget at the surface, because of the dominant role of the liquid water in CRF. Yet, the coupling between Arctic low clouds and the surface is complex and has strong impacts on ABL. Studying GPS/COSMIC radio occultation (RO) refractivity profiles in the Arctic coldest and driest months, we successfully derived ABL inversion height and surface-based inversion (SBI) frequency, and they were anti-correlated over the Arctic Ocean. For the late summer and early fall season, we further analyzed Japanese R/V Mirai ship measurements and found that the open-ocean surface sensible heat flux (SSHF) can explain 10 % of the ABL height variability, whereas mechanisms such as cloud-driven turbulence appear to be dominant. Contrary to previous speculation, the efficiency of turbulent heat exchange is low. The SSHF contribution to ABL mixing is significant during the uplift (low-pressure) followed by the highly stable (stratus cloud) regime.

Methane rain on Titan

NASA Technical Reports Server (NTRS)

Toon, Owen B.; Mckay, Christopher P.; Courtin, Regis; Ackerman, Thomas P.

1988-01-01

The atmosphere of Titan is characterized by means of model computations based on Voyager IRIS IR spectra and published data from laboratory determinations of absorption coefficients and cloud refractive indices. The results are presented in tables and graphs, and it is pointed out that the presence of Ar is not required in the model. Particular attention is given to the role of CH4, which is found to form patchy clouds (with particle radii of 50 microns or greater and visible/IR optical depths of 2-5) at altitudes up to about 30 km. The mechanisms by which such rain-sized particles could form are discussed, and it is suggested that the observed 500-600/cm spectrum is affected much less by the CH4 clouds than by H2 or variations in the temperature of the high-altitude haze.

Inverted Polarity Thunderstorms Linked with Elevated Cloud Base Height

NASA Astrophysics Data System (ADS)

Cummins, K. L.; Williams, E.

2016-12-01

The great majority of thunderstorms worldwide exhibit gross positive dipole structure, produce intracloud lightning that reduces this positive dipole (positive intracloud flashes), and produce negative cloud-to-ground lightning from the lower negative end of this dipole. During the STEPS experiment in 2000 much new evidence for thunderstorms (or cells within multi-cellular storms) with inverted polarity came to light, both from balloon soundings of electric field and from LMA analysis. Many of the storms with inverted polarity cells developed in eastern Colorado. Fleenor et al. (2009) followed up after STEPS to document a dominance of positive polarity CG lightning in many of these cases. In the present study, surface thermodynamic observations (temperature and dew point temperature) have been used to estimate the cloud base heights and temperatures at the time of the Fleenor et al. lightning observations. It was found that when more than 90% of the observed CG lightning polarity within a storm is negative, the cloud base heights were low (2000 m AGL or lower, and warmer, with T>10 C), and when more than 90% of the observed CG lightning within a storm was positive, the cloud base heights were high (3000 m AGL or higher, and colder, with T< 2 C). Multi-cellular storms or temporally-evolving storms with mixed polarity were generally associated with intermediate cloud base heights. These findings on inverted polarity thunderstorms are remarkably consistent with results in other parts of the world where strong instability prevails in the presence of high cloud base height: the plateau regions of China (Liu et al., 1989; Qie et al., 2005), and in pre-monsoon India (Pawar et al., 2016), particularly when mixed polarity cases are excluded. Calculations of adiabatic cloud water content for lifting from near 0 oC cast some doubt on earlier speculation (Williams et al., 2005) that the graupel particles in these inverted polarity storms attain a wet growth condition, and so exhibit positive charging following laboratory experiments. This mechanism will be contrasted with the possibility of positive graupel charging associated with small droplet sizes (consistent with high cloud base) or through involvement of ice nuclei (Pawar et al., 2016) in the semiarid environments that frequently accompany inverted polarity storms.

Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.

2016-12-01

Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of representations of large-scale moisture transport, cloud microphysics, ice nucleation, and cumulus detrainment in order to improve the mixed-phase transition in GCMs.

Analysis of the Dryden Wet Bulb GLobe Temperature Algorithm for White Sands Missile Range

NASA Technical Reports Server (NTRS)

LaQuay, Ryan Matthew

2011-01-01

In locations where workforce is exposed to high relative humidity and light winds, heat stress is a significant concern. Such is the case at the White Sands Missile Range in New Mexico. Heat stress is depicted by the wet bulb globe temperature, which is the official measurement used by the American Conference of Governmental Industrial Hygienists. The wet bulb globe temperature is measured by an instrument which was designed to be portable and needing routine maintenance. As an alternative form for measuring the wet bulb globe temperature, algorithms have been created to calculate the wet bulb globe temperature from basic meteorological observations. The algorithms are location dependent; therefore a specific algorithm is usually not suitable for multiple locations. Due to climatology similarities, the algorithm developed for use at the Dryden Flight Research Center was applied to data from the White Sands Missile Range. A study was performed that compared a wet bulb globe instrument to data from two Surface Atmospheric Measurement Systems that was applied to the Dryden wet bulb globe temperature algorithm. The period of study was from June to September of2009, with focus being applied from 0900 to 1800, local time. Analysis showed that the algorithm worked well, with a few exceptions. The algorithm becomes less accurate to the measurement when the dew point temperature is over 10 Celsius. Cloud cover also has a significant effect on the measured wet bulb globe temperature. The algorithm does not show red and black heat stress flags well due to shorter time scales of such events. The results of this study show that it is plausible that the Dryden Flight Research wet bulb globe temperature algorithm is compatible with the White Sands Missile Range, except for when there are increased dew point temperatures and cloud cover or precipitation. During such occasions, the wet bulb globe temperature instrument would be the preferred method of measurement. Out of the 30 dates examined, 23 fell under the category of having good accuracy.

Analysis of a jet stream induced gravity wave associated with an observed stratospheric ice cloud over Greenland

NASA Astrophysics Data System (ADS)

Buss, S.; Hertzog, A.; Hostettler, C.; Bui, T. B.; Lüthi, D.; Wernli, H.

2004-08-01

A polar stratospheric ice cloud (PSC type II) was observed by airborne lidar above Greenland on 14 January 2000. It was the unique observation of an ice cloud over Greenland during the SOLVE/THESEO 2000 campaign. Mesoscale simulations with the hydrostatic HRM model are presented which, in contrast to global analyses, are capable to produce a vertically propagating gravity wave that induces the low temperatures at the level of the PSC afforded for the ice formation. The simulated minimum temperature is ~8 K below the driving analyses and ~4.5 K below the frost point, exactly coinciding with the location of the observed ice cloud. Despite the high elevations of the Greenland orography the simulated gravity wave is not a mountain wave. Analyses of the horizontal wind divergence, of the background wind profiles, of backward gravity wave ray-tracing trajectories, of HRM experiments with reduced Greenland topography and of several diagnostics near the tropopause level provide evidence that the wave is emitted from an intense, rapidly evolving, anticyclonically curved jet stream. The precise physical process responsible for the wave emission could not be identified definitely, but geostrophic adjustment and shear instability are likely candidates.

In order to evaluate the potential frequency of such non-orographic polar stratospheric cloud events, the non-linear balance equation diagnostic is performed for the winter 1999/2000. It indicates that ice-PSCs are only occasionally generated by gravity waves emanating from spontaneous adjustment.

Cloud point extraction and flame atomic absorption spectrometric determination of cadmium and nickel in drinking and wastewater samples.

PubMed

Naeemullah; Kazi, Tasneem G; Shah, Faheem; Afridi, Hassan I; Baig, Jameel Ahmed; Soomro, Abdul Sattar

2013-01-01

A simple method for the preconcentration of cadmium (Cd) and nickel (Ni) in drinking and wastewater samples was developed. Cloud point extraction has been used for the preconcentration of both metals, after formation of complexes with 8-hydroxyquinoline (8-HQ) and extraction with the surfactant octylphenoxypolyethoxyethanol (Triton X-114). Dilution of the surfactant-rich phase with acidified ethanol was performed after phase separation, and the Cd and Ni contents were measured by flame atomic absorption spectrometry. The experimental variables, such as pH, amounts of reagents (8-HQ and Triton X-114), temperature, incubation time, and sample volume, were optimized. After optimization of the complexation and extraction conditions, enhancement factors of 80 and 61, with LOD values of 0.22 and 0.52 microg/L, were obtained for Cd and Ni, respectively. The proposed method was applied satisfactorily for the determination of both elements in drinking and wastewater samples.

Determination of trace inorganic mercury species in water samples by cloud point extraction and UV-vis spectrophotometry.

PubMed

Ulusoy, Halil Ibrahim

2014-01-01

A new micelle-mediated extraction method was developed for preconcentration of ultratrace Hg(II) ions prior to spectrophotometric determination. 2-(2'-Thiazolylazo)-p-cresol (TAC) and Ponpe 7.5 were used as the chelating agent and nonionic surfactant, respectively. Hg(II) ions form a hydrophobic complex with TAC in a micelle medium. The main factors affecting cloud point extraction efficiency, such as pH of the medium, concentrations of TAC and Ponpe 7.5, and equilibration temperature and time, were investigated in detail. An overall preconcentration factor of 33.3 was obtained upon preconcentration of a 50 mL sample. The LOD obtained under the optimal conditions was 0.86 microg/L, and the RSD for five replicate measurements of 100 microg/L Hg(II) was 3.12%. The method was successfully applied to the determination of Hg in environmental water samples.

Hydrogen axion star: metallic hydrogen bound to a QCD axion BEC

DOE PAGES

Bai, Yang; Barger, Vernon; Berger, Joshua

2016-12-23

As a cold dark matter candidate, the QCD axion may form Bose-Einstein condensates, called axion stars, with masses around 10 -11M⊙ . In this paper, we point out that a brand new astrophysical object, a Hydrogen Axion Star (HAS), may well be formed by ordinary baryonic matter becoming gravitationally bound to an axion star. Here, we study the properties of the HAS and nd that the hydrogen cloud has a high pressure and temperature in the center and is likely in the liquid metallic hydrogen state. Because of the high particle number densities for both the axion star and themore » hydrogen cloud, the feeble interaction between axion and hydrogen can still generate enough internal power, around 10 13W (m a/=5 meV) 4, to make these objects luminous point sources. Furthermore, high resolution ultraviolet, optical and infrared telescopes can discover HAS via black-body radiation.« less

Hydrogen axion star: metallic hydrogen bound to a QCD axion BEC

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

Bai, Yang; Barger, Vernon; Berger, Joshua

As a cold dark matter candidate, the QCD axion may form Bose-Einstein condensates, called axion stars, with masses around 10 -11M⊙ . In this paper, we point out that a brand new astrophysical object, a Hydrogen Axion Star (HAS), may well be formed by ordinary baryonic matter becoming gravitationally bound to an axion star. Here, we study the properties of the HAS and nd that the hydrogen cloud has a high pressure and temperature in the center and is likely in the liquid metallic hydrogen state. Because of the high particle number densities for both the axion star and themore » hydrogen cloud, the feeble interaction between axion and hydrogen can still generate enough internal power, around 10 13W (m a/=5 meV) 4, to make these objects luminous point sources. Furthermore, high resolution ultraviolet, optical and infrared telescopes can discover HAS via black-body radiation.« less

Climatic Implications of the Observed Temperature Dependence of the Liquid Water Path of Low Clouds

NASA Technical Reports Server (NTRS)

DelGenio, Anthony

1999-01-01

The uncertainty in the global climate sensitivity to an equilibrium doubling of carbon dioxide is often stated to be 1.5-4.5 K, largely due to uncertainties in cloud feedbacks. The lower end of this range is based on the assumption or prediction in some GCMs that cloud liquid water behaves adiabatically, thus implying that cloud optical thickness will increase in a warming climate if the physical thickness of clouds is invariant. Satellite observations of low-level cloud optical thickness and liquid water path have challenged this assumption, however, at low and middle latitudes. We attempt to explain the satellite results using four years of surface remote sensing data from the Atmospheric Radiation Measurements (ARM) Cloud And Radiation Testbed (CART) site in the Southern Great Plains. We find that low cloud liquid water path is insensitive to temperature in winter but strongly decreases with temperature in summer. The latter occurs because surface relative humidity decreases with warming, causing cloud base to rise and clouds to geometrically thin. Meanwhile, inferred liquid water contents hardly vary with temperature, suggesting entrainment depletion. Physically, the temperature dependence appears to represent a transition from higher probabilities of stratified boundary layers at cold temperatures to a higher incidence of convective boundary layers at warm temperatures. The combination of our results and the earlier satellite findings imply that the minimum climate sensitivity should be revised upward from 1.5 K.

Relationship Between Cirrus Particle Size and Cloud Top Temperature

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Chou, Joyce; Welch, Ronald M.

1997-01-01

The relationship between cirrus particle size and cloud top temperature is surveyed on a near-global scale. The cirrus particle size is retrieved assuming ice crystals are hexagonal columns and the cloud top temperature and the radiances in channel 1 and 3 of AVHRR used to retrieve ice particle sizes are from ISCCP product. The results show that for thick clouds over North America, the relation between particle size and cloud top temperature is consistent with a summary of this relationship based on aircraft measurement over that region for thick clouds. However, this relationship is not universal for other regions especially for for tropical zone, which has been found by other in situ measurements.

Filtering Photogrammetric Point Clouds Using Standard LIDAR Filters Towards DTM Generation

NASA Astrophysics Data System (ADS)

Zhang, Z.; Gerke, M.; Vosselman, G.; Yang, M. Y.

2018-05-01

Digital Terrain Models (DTMs) can be generated from point clouds acquired by laser scanning or photogrammetric dense matching. During the last two decades, much effort has been paid to developing robust filtering algorithms for the airborne laser scanning (ALS) data. With the point cloud quality from dense image matching (DIM) getting better and better, the research question that arises is whether those standard Lidar filters can be used to filter photogrammetric point clouds as well. Experiments are implemented to filter two dense matching point clouds with different noise levels. Results show that the standard Lidar filter is robust to random noise. However, artefacts and blunders in the DIM points often appear due to low contrast or poor texture in the images. Filtering will be erroneous in these locations. Filtering the DIM points pre-processed by a ranking filter will bring higher Type II error (i.e. non-ground points actually labelled as ground points) but much lower Type I error (i.e. bare ground points labelled as non-ground points). Finally, the potential DTM accuracy that can be achieved by DIM points is evaluated. Two DIM point clouds derived by Pix4Dmapper and SURE are compared. On grassland dense matching generates points higher than the true terrain surface, which will result in incorrectly elevated DTMs. The application of the ranking filter leads to a reduced bias in the DTM height, but a slightly increased noise level.

Cloud top structure of Venus revealed by Subaru/COMICS mid-infrared images

NASA Astrophysics Data System (ADS)

Sato, T. M.; Sagawa, H.; Kouyama, T.; Mitsuyama, K.; Satoh, T.; Ohtsuki, S.; Ueno, M.; Kasaba, Y.; Nakamura, M.; Imamura, T.

2014-11-01

We have investigated the cloud top structure of Venus by analyzing ground-based images taken at the mid-infrared wavelengths of 8.66 μm and 11.34 μm. Venus at a solar phase angle of ∼90°, with the morning terminator in view, was observed by the Cooled Mid-Infrared Camera and Spectrometer (COMICS), mounted on the 8.2-m Subaru Telescope, during the period October 25-29, 2007. The disk-averaged brightness temperatures for the observation period are ∼230 K and ∼238 K at 8.66 μm and 11.34 μm, respectively. The obtained images with good signal-to-noise ratio and with high spatial resolution (∼200 km at the sub-observer point) provide several important findings. First, we present observational evidence, for the first time, of the possibility that the westward rotation of the polar features (the hot polar spots and the surrounding cold collars) is synchronized between the northern and southern hemispheres. Second, after high-pass filtering, the images reveal that streaks and mottled and patchy patterns are distributed over the entire disk, with typical amplitudes of ∼0.5 K, and vary from day to day. The detected features, some of which are similar to those seen in past UV images, result from inhomogeneities of both the temperature and the cloud top altitude. Third, the equatorial center-to-limb variations of brightness temperatures have a systematic day-night asymmetry, except those on October 25, that the dayside brightness temperatures are higher than the nightside brightness temperatures by 0-4 K under the same viewing geometry. Such asymmetry would be caused by the propagation of the migrating semidiurnal tide. Finally, by applying the lapse rates deduced from previous studies, we demonstrate that the equatorial center-to-limb curves in the two spectral channels give access to two parameters: the cloud scale height H and the cloud top altitude zc. The acceptable models for data on October 25 are obtained at H = 2.4-4.3 km and zc = 66-69 km; this supports previous results determined from spacecraft observations.

Remote Sensing the Vertical Profile of Cloud Droplet Effective Radius, Thermodynamic Phase, and Temperature

NASA Technical Reports Server (NTRS)

Martins, J. V.; Marshak, A.; Remer, L. A.; Rosenfeld, D.; Kaufman, Y. J.; Fernandez-Borda, R.; Koren, I.; Correia, A. L.; Zubko, V.; Artaxo, P.

2011-01-01

Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

Impact of Surface Active Ionic Liquids on the Cloud Points of Nonionic Surfactants and the Formation of Aqueous Micellar Two-Phase Systems.

PubMed

Vicente, Filipa A; Cardoso, Inês S; Sintra, Tânia E; Lemus, Jesus; Marques, Eduardo F; Ventura, Sónia P M; Coutinho, João A P

2017-09-21

Aqueous micellar two-phase systems (AMTPS) hold a large potential for cloud point extraction of biomolecules but are yet poorly studied and characterized, with few phase diagrams reported for these systems, hence limiting their use in extraction processes. This work reports a systematic investigation of the effect of different surface-active ionic liquids (SAILs)-covering a wide range of molecular properties-upon the clouding behavior of three nonionic Tergitol surfactants. Two different effects of the SAILs on the cloud points and mixed micelle size have been observed: ILs with a more hydrophilic character and lower critical packing parameter (CPP < 1 / 2 ) lead to the formation of smaller micelles and concomitantly increase the cloud points; in contrast, ILs with a more hydrophobic character and higher CPP (CPP ≥ 1) induce significant micellar growth and a decrease in the cloud points. The latter effect is particularly interesting and unusual for it was accepted that cloud point reduction is only induced by inorganic salts. The effects of nonionic surfactant concentration, SAIL concentration, pH, and micelle ζ potential are also studied and rationalized.

High Lapse Rates in AIRS Retrieved Temperatures in Cold Air Outbreaks

NASA Technical Reports Server (NTRS)

Fetzer, Eric J.; Kahn, Brian; Olsen, Edward T.; Fishbein, Evan

2004-01-01

The Atmospheric Infrared Sounder (AIRS) experiment, on NASA's Aqua spacecraft, uses a combination of infrared and microwave observations to retrieve cloud and surface properties, plus temperature and water vapor profiles comparable to radiosondes throughout the troposphere, for cloud cover up to 70%. The high spectral resolution of AIRS provides sensitivity to important information about the near-surface atmosphere and underlying surface. A preliminary analysis of AIRS temperature retrievals taken during January 2003 reveals extensive areas of superadiabatic lapse rates in the lowest kilometer of the atmosphere. These areas are found predominantly east of North America over the Gulf Stream, and, off East Asia over the Kuroshio Current. Accompanying the high lapse rates are low air temperatures, large sea-air temperature differences, and low relative humidities. Imagery from a Visible / Near Infrared instrument on the AIRS experiment shows accompanying clouds. These lines of evidence all point to shallow convection in the bottom layer of a cold air mass overlying warm water, with overturning driven by heat flow from ocean to atmosphere. An examination of operational radiosondes at six coastal stations in Japan shows AIRS to be oversensitive to lower tropospheric lapse rates due to systematically warm near-surface air temperatures. The bias in near-surface air temperature is seen to be independent of sea surface temperature, however. AIRS is therefore sensitive to air-sea temperature difference, but with a warm atmospheric bias. A regression fit to radiosondes is used to correct AIRS near-surface retrieved temperatures, and thereby obtain an estimate of the true atmosphere-ocean thermal contrast in five subtropical regions across the north Pacific. Moving eastward, we show a systematic shift in this air-sea temperature differences toward more isothermal conditions. These results, while preliminary, have implications for our understanding of heat flow from ocean to atmosphere. We anticipate future improvements in the AIRS retrieval algorithm will lead to improved understanding of the exchange of sensible and latent heat from ocean to atmosphere, and more realistic near-surface lapse rates.

Development of methods for inferring cloud thickness and cloud-base height from satellite radiance data

NASA Technical Reports Server (NTRS)

Smith, William L., Jr.; Minnis, Patrick; Alvarez, Joseph M.; Uttal, Taneil; Intrieri, Janet M.; Ackerman, Thomas P.; Clothiaux, Eugene

1993-01-01

Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Design of relative motion and attitude profiles for three-dimensional resident space object imaging with a laser rangefinder

NASA Astrophysics Data System (ADS)

Nayak, M.; Beck, J.; Udrea, B.

This paper focuses on the aerospace application of a single beam laser rangefinder (LRF) for 3D imaging, shape detection, and reconstruction in the context of a space-based space situational awareness (SSA) mission scenario. The primary limitation to 3D imaging from LRF point clouds is the one-dimensional nature of the single beam measurements. A method that combines relative orbital motion and scanning attitude motion to generate point clouds has been developed and the design and characterization of multiple relative motion and attitude maneuver profiles are presented. The target resident space object (RSO) has the shape of a generic telecommunications satellite. The shape and attitude of the RSO are unknown to the chaser satellite however, it is assumed that the RSO is un-cooperative and has fixed inertial pointing. All sensors in the metrology chain are assumed ideal. A previous study by the authors used pure Keplerian motion to perform a similar 3D imaging mission at an asteroid. A new baseline for proximity operations maneuvers for LRF scanning, based on a waypoint adaptation of the Hill-Clohessy-Wiltshire (HCW) equations is examined. Propellant expenditure for each waypoint profile is discussed and combinations of relative motion and attitude maneuvers that minimize the propellant used to achieve a minimum required point cloud density are studied. Both LRF strike-point coverage and point cloud density are maximized; the capability for 3D shape registration and reconstruction from point clouds generated with a single beam LRF without catalog comparison is proven. Next, a method of using edge detection algorithms to process a point cloud into a 3D modeled image containing reconstructed shapes is presented. Weighted accuracy of edge reconstruction with respect to the true model is used to calculate a qualitative “ metric” that evaluates effectiveness of coverage. Both edge recognition algorithms and the metric are independent of point cloud densit- , therefore they are utilized to compare the quality of point clouds generated by various attitude and waypoint command profiles. The RSO model incorporates diverse irregular protruding shapes, such as open sensor covers, instrument pods and solar arrays, to test the limits of the algorithms. This analysis is used to mathematically prove that point clouds generated by a single-beam LRF can achieve sufficient edge recognition accuracy for SSA applications, with meaningful shape information extractable even from sparse point clouds. For all command profiles, reconstruction of RSO shapes from the point clouds generated with the proposed method are compared to the truth model and conclusions are drawn regarding their fidelity.

An Efficient Method to Create Digital Terrain Models from Point Clouds Collected by Mobile LiDAR Systems

NASA Astrophysics Data System (ADS)

Gézero, L.; Antunes, C.

2017-05-01

The digital terrain models (DTM) assume an essential role in all types of road maintenance, water supply and sanitation projects. The demand of such information is more significant in developing countries, where the lack of infrastructures is higher. In recent years, the use of Mobile LiDAR Systems (MLS) proved to be a very efficient technique in the acquisition of precise and dense point clouds. These point clouds can be a solution to obtain the data for the production of DTM in remote areas, due mainly to the safety, precision, speed of acquisition and the detail of the information gathered. However, the point clouds filtering and algorithms to separate "terrain points" from "no terrain points", quickly and consistently, remain a challenge that has caught the interest of researchers. This work presents a method to create the DTM from point clouds collected by MLS. The method is based in two interactive steps. The first step of the process allows reducing the cloud point to a set of points that represent the terrain's shape, being the distance between points inversely proportional to the terrain variation. The second step is based on the Delaunay triangulation of the points resulting from the first step. The achieved results encourage a wider use of this technology as a solution for large scale DTM production in remote areas.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

10-Year Observations of Cloud and Surface Longwave Radiation at Ny-Ålesund, Svalbard

NASA Astrophysics Data System (ADS)

Yeo, H.; Kim, S. W.; Kim, B. M.; Kim, J. H.; Shiobara, M.; Choi, T. J.; Son, S. W.; Kim, M. H.; Jeong, J. H.; Kim, S. J.

2015-12-01

Arctic clouds play a key role in surface radiation budget and may influence sea ice and snow melting. In this study, 10-year (2004-2013) observations of cloud from Micro-Pulse Lidar (MPL) and surface longwave (LW) radiation at Ny-Ålesund, Svalbard are analyzed to investigate cloud radiative effect. The cloud fraction (CF) derived from MPL shows distinct monthly variation, having higher CF (0.90) in summer and lower CF (0.79) in winter. Downward longwave radiation (DLW) during wintertime (Nov., Dec., Jan., and Feb.) decreases as cloud base height (CBH) increases. The DLW for CBH < 1km (264.7±35.4 W m-2) is approximately 1.46 times larger than that for cloud-free (181.8±25.8 W m-2) conditions. The temperature difference (ΔT) and DLW difference (ΔDLW), which are calculated as the difference of monthly mean temperature and DLW between all-sky and cloud-free conditions, are positively correlated (R2 = 0.83). This implies that an increase of DLW may influence surface warming, which can result in snow and sea ice melting. However, dramatic changes in surface temperature, cloud and DLW are observed with a time scale of a few days. The averaged surface temperature on the presence of low-level clouds (CBH < 2km) and under cloud-free conditions are estimated to be -6.9±6.1°C and -14.5±5.7°C, respectively. The duration of low-level clouds, showing relatively high DLW and high surface temperature, is about 2.5 days. This suggests that DLW induced by low-level clouds may not have a critical effect on surface temperature rising and sea ice melting.

Effect of target color and scanning geometry on terrestrial LiDAR point-cloud noise and plane fitting

NASA Astrophysics Data System (ADS)

Bolkas, Dimitrios; Martinez, Aaron

2018-01-01

Point-cloud coordinate information derived from terrestrial Light Detection And Ranging (LiDAR) is important for several applications in surveying and civil engineering. Plane fitting and segmentation of target-surfaces is an important step in several applications such as in the monitoring of structures. Reliable parametric modeling and segmentation relies on the underlying quality of the point-cloud. Therefore, understanding how point-cloud errors affect fitting of planes and segmentation is important. Point-cloud intensity, which accompanies the point-cloud data, often goes hand-in-hand with point-cloud noise. This study uses industrial particle boards painted with eight different colors (black, white, grey, red, green, blue, brown, and yellow) and two different sheens (flat and semi-gloss) to explore how noise and plane residuals vary with scanning geometry (i.e., distance and incidence angle) and target-color. Results show that darker colors, such as black and brown, can produce point clouds that are several times noisier than bright targets, such as white. In addition, semi-gloss targets manage to reduce noise in dark targets by about 2-3 times. The study of plane residuals with scanning geometry reveals that, in many of the cases tested, residuals decrease with increasing incidence angles, which can assist in understanding the distribution of plane residuals in a dataset. Finally, a scheme is developed to derive survey guidelines based on the data collected in this experiment. Three examples demonstrate that users should consider instrument specification, required precision of plane residuals, required point-spacing, target-color, and target-sheen, when selecting scanning locations. Outcomes of this study can aid users to select appropriate instrumentation and improve planning of terrestrial LiDAR data-acquisition.

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.

CloudSat Overflight of Hurricane Bud

NASA Image and Video Library

2006-07-13

The image at the top of figure 1 is from a geostationary imager. The colors relate to the temperature of the clouds. The higher the clouds, the lower the temperature. The highest, coldest clouds are located near the center of the hurricane.

Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

NASA Astrophysics Data System (ADS)

Irion, Fredrick W.; Kahn, Brian H.; Schreier, Mathias M.; Fetzer, Eric J.; Fishbein, Evan; Fu, Dejian; Kalmus, Peter; Wilson, R. Chris; Wong, Sun; Yue, Qing

2018-02-01

Single-footprint Atmospheric Infrared Sounder spectra are used in an optimal estimation-based algorithm (AIRS-OE) for simultaneous retrieval of atmospheric temperature, water vapor, surface temperature, cloud-top temperature, effective cloud optical depth and effective cloud particle radius. In a departure from currently operational AIRS retrievals (AIRS V6), cloud scattering and absorption are in the radiative transfer forward model and AIRS single-footprint thermal infrared data are used directly rather than cloud-cleared spectra (which are calculated using nine adjacent AIRS infrared footprints). Coincident MODIS cloud data are used for cloud a priori data. Using single-footprint spectra improves the horizontal resolution of the AIRS retrieval from ˜ 45 to ˜ 13.5 km at nadir, but as microwave data are not used, the retrieval is not made at altitudes below thick clouds. An outline of the AIRS-OE retrieval procedure and information content analysis is presented. Initial comparisons of AIRS-OE to AIRS V6 results show increased horizontal detail in the water vapor and relative humidity fields in the free troposphere above the clouds. Initial comparisons of temperature, water vapor and relative humidity profiles with coincident radiosondes show good agreement. Future improvements to the retrieval algorithm, and to the forward model in particular, are discussed.

Water Vapor, Temperature, and Ice Particles in Polar Mesosphere as Measured by SABER/TIMED and OSIRIS/Odin Instruments

NASA Technical Reports Server (NTRS)

Feofilov, A. G.; Petelina, S. V.; Kutepov, A. A.; Pesnell, W. D.; Goldberg, R. A.

2009-01-01

Although many new details on the properties of mesospheric ice particles that farm Polar Mesospheric Clouds (PMCs) and also cause polar mesospheric summer echoes have been recently revealed, certain aspects of mesospheric ice microphysics and dynamics still remain open. The detailed relation between PMC parameters and properties of their environment, as well as interseasonal and interhemispheric differences and trends in PMC properties that are possibly related to global change, are among those open questions. In this work, mesospheric temperature and water vapor concentration measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on board the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite are used to study the properties of PMCs with respect to the surrounding atmosphere. The cloud parameters, namely location, brightness, and altitude, are obtained from the observations made by the Optical Spectrograph and Infrared Imager System (OSIRIS) on the Odin satellite. About a thousand of simultaneous common volume measurements made by SABER and OSIRIS in both hemispheres from 2002 until 2008 are used. The correlation between PMC brightness (and occurrence rate) and temperatures at PMC altitudes and at the mesopause is analysed. The relation between PMC parameters, frost point temperature, and gaseous water vapor content in and below the cloud is also discussed. Interseasonal and interhemispheric differences and trends in the above parameters, as well as in PMC peak altitudes and mesopause altitudes are evaluated.

The Radiative Effects of Martian Water Ice Clouds on the Local Atmospheric Temperature Profile

NASA Technical Reports Server (NTRS)

Colaprete, Anthony; Toon, Owen B.

2000-01-01

Mars Pathfinder made numerous discoveries, one of which was a deep temperature inversion that extended from about 15 km down to 8 km above the surface. It has been suggested by Haberle et al. (1999. J. Geophys. Res. 104, 8957-8974.) that radiative cooling by a water ice cloud may generate such an inversion. Clouds can strongly affect the local air temperature due to their ability to radiate efficiently in the infrared and due to the low air mass of the martian atmosphere, which allows the temperature to change during the relatively short lifetime of a cloud. We utilize a time-dependent microphysical aerosol model coupled to a radiative--convective model to explore the effects water ice clouds have on the local martian temperature profile. We constrain the dust and water vapor abundance using data from the Viking Missions and Mars Pathfinder. Water t ice clouds with visible optical depths of r > 0.1 form readily in these simulations. These clouds alter the local air temperature directly, through infrared cooling, and indirectly, by redistributing atmospheric dust. With this model we are able to reproduce the temperature inversions observed by Mars Pathfinder and Mars Global t Surveyor 2000 Academic Press

Temporally consistent segmentation of point clouds

NASA Astrophysics Data System (ADS)

Owens, Jason L.; Osteen, Philip R.; Daniilidis, Kostas

2014-06-01

We consider the problem of generating temporally consistent point cloud segmentations from streaming RGB-D data, where every incoming frame extends existing labels to new points or contributes new labels while maintaining the labels for pre-existing segments. Our approach generates an over-segmentation based on voxel cloud connectivity, where a modified k-means algorithm selects supervoxel seeds and associates similar neighboring voxels to form segments. Given the data stream from a potentially mobile sensor, we solve for the camera transformation between consecutive frames using a joint optimization over point correspondences and image appearance. The aligned point cloud may then be integrated into a consistent model coordinate frame. Previously labeled points are used to mask incoming points from the new frame, while new and previous boundary points extend the existing segmentation. We evaluate the algorithm on newly-generated RGB-D datasets.

Volcanic explosion clouds - Density, temperature, and particle content estimates from cloud motion

NASA Technical Reports Server (NTRS)

Wilson, L.; Self, S.

1980-01-01

Photographic records of 10 vulcanian eruption clouds produced during the 1978 eruption of Fuego Volcano in Guatemala have been analyzed to determine cloud velocity and acceleration at successive stages of expansion. Cloud motion is controlled by air drag (dominant during early, high-speed motion) and buoyancy (dominant during late motion when the cloud is convecting slowly). Cloud densities in the range 0.6 to 1.2 times that of the surrounding atmosphere were obtained by fitting equations of motion for two common cloud shapes (spheres and vertical cylinders) to the observed motions. Analysis of the heat budget of a cloud permits an estimate of cloud temperature and particle weight fraction to be made from the density. Model results suggest that clouds generally reached temperatures within 10 K of that of the surrounding air within 10 seconds of formation and that dense particle weight fractions were less than 2% by this time. The maximum sizes of dense particles supported by motion in the convecting clouds range from 140 to 1700 microns.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree

NASA Astrophysics Data System (ADS)

Kang, Q.; Huang, G.; Yang, S.

2018-04-01

Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.

Temperature histories in liquid and solid polar stratospheric cloud formation

NASA Astrophysics Data System (ADS)

Larsen, Niels; Knudsen, Bjørn M.; Rosen, James M.; Kjome, Norman T.; Neuber, Roland; Kyrö, Esko

1997-10-01

Polar stratospheric clouds (PSCs) have been observed by balloonborne backscatter sondes from Alert, Thule, Heiss Island, Scoresbysund, Sodankylä, Søndre Strømfjord, and Ny Ȧlesund during winters 1989, 1990, 1995, and 1996 in 30 flights. The observations can be categorized into two main groups: type 1a and type 1b PSC particles. Type 1b PSCs show the characteristics expected from liquid ternary solution (HNO3/H2SO4/H2O) particles, consistent with model simulations. Type 1a PSCs are observed at all temperatures below the condensation temperature TNAT of nitric acid trihydrate (NAT), consistent with solid NAT composition. Air parcel trajectories have been calculated for all observations to provide synoptic temperature histories of the observed particles. A number of cases have been identified, where the particles have experienced temperatures close to or above the sulfuric acid tetrahydrate melting temperatures within 20 days prior to observation. This assures a knowledge of the physical phase (liquid) of the particles at this time, prior to observation. The subsequent synoptic temperature histories, between melting and the time of observation, show pronounced differences for type 1a and type 1b PSC particles, indicating the qualitative temperature conditions, necessary to generate solid type 1a PSCs. The temperature histories of type 1b particles show smoothly, in most cases monotonic, decreasing temperatures. The temperature can apparently decrease to the frost point without causing the particles to freeze. The type 1b PSC particles are mostly observed shortly after entering a cold region. The observed type 1a particles have spent several days at temperatures close to or below TNAT prior to observation, often associated with several synoptic temperature oscillations around TNAT, and the particles are observed in aged clouds. It appears that the PSC particles may freeze, if they experience synoptic temperatures below TNAT with a duration of at least 1 day, possibly accompanied by several temperature oscillations. However, liquid particles that experience a smooth cooling, even to very low temperatures, or single smooth cooling/heating below TNAT without synoptic temperature fluctuations do not seem to freeze.

Prototype methodology for obtaining cloud seeding guidance from HRRR model data

NASA Astrophysics Data System (ADS)

Dawson, N.; Blestrud, D.; Kunkel, M. L.; Waller, B.; Ceratto, J.

2017-12-01

Weather model data, along with real time observations, are critical to determine whether atmospheric conditions are prime for super-cooled liquid water during cloud seeding operations. Cloud seeding groups can either use operational forecast models, or run their own model on a computer cluster. A custom weather model provides the most flexibility, but is also expensive. For programs with smaller budgets, openly-available operational forecasting models are the de facto method for obtaining forecast data. The new High-Resolution Rapid Refresh (HRRR) model (3 x 3 km grid size), developed by the Earth System Research Laboratory (ESRL), provides hourly model runs with 18 forecast hours per run. While the model cannot be fine-tuned for a specific area or edited to provide cloud-seeding-specific output, model output is openly available on a near-real-time basis. This presentation focuses on a prototype methodology for using HRRR model data to create maps which aid in near-real-time cloud seeding decision making. The R programming language is utilized to run a script on a Windows® desktop/laptop computer either on a schedule (such as every half hour) or manually. The latest HRRR model run is downloaded from NOAA's Operational Model Archive and Distribution System (NOMADS). A GRIB-filter service, provided by NOMADS, is used to obtain surface and mandatory pressure level data for a subset domain which greatly cuts down on the amount of data transfer. Then, a set of criteria, identified by the Idaho Power Atmospheric Science Group, is used to create guidance maps. These criteria include atmospheric stability (lapse rates), dew point depression, air temperature, and wet bulb temperature. The maps highlight potential areas where super-cooled liquid water may exist, reasons as to why cloud seeding should not be attempted, and wind speed at flight level.

Determination of carcinogenic herbicides in milk samples using green non-ionic silicone surfactant of cloud point extraction and spectrophotometry.

PubMed

Mohd, N I; Zain, N N M; Raoov, M; Mohamad, S

2018-04-01

A new cloud point methodology was successfully used for the extraction of carcinogenic pesticides in milk samples as a prior step to their determination by spectrophotometry. In this work, non-ionic silicone surfactant, also known as 3-(3-hydroxypropyl-heptatrimethylxyloxane), was chosen as a green extraction solvent because of its structure and properties. The effect of different parameters, such as the type of surfactant, concentration and volume of surfactant, pH, salt, temperature, incubation time and water content on the cloud point extraction of carcinogenic pesticides such as atrazine and propazine, was studied in detail and a set of optimum conditions was established. A good correlation coefficient ( R 2 ) in the range of 0.991-0.997 for all calibration curves was obtained. The limit of detection was 1.06 µg l -1 (atrazine) and 1.22 µg l -1 (propazine), and the limit of quantitation was 3.54 µg l -1 (atrazine) and 4.07 µg l -1 (propazine). Satisfactory recoveries in the range of 81-108% were determined in milk samples at 5 and 1000 µg l -1 , respectively, with low relative standard deviation, n  = 3 of 0.301-7.45% in milk matrices. The proposed method is very convenient, rapid, cost-effective and environmentally friendly for food analysis.

Ultrasonically Modified Amended-Cloud Point Extraction for Simultaneous Pre-Concentration of Neonicotinoid Insecticide Residues.

PubMed

Kachangoon, Rawikan; Vichapong, Jitlada; Burakham, Rodjana; Santaladchaiyakit, Yanawath; Srijaranai, Supalax

2018-05-12

An effective pre-concentration method, namely amended-cloud point extraction (CPE), has been developed for the extraction and pre-concentration of neonicotinoid insecticide residues. The studied analytes including clothianidin, imidacloprid, acetamiprid, thiamethoxam and thiacloprid were chosen as a model compound. The amended-CPE procedure included two cloud point processes. Triton™ X-114 was used to extract neonicotinoid residues into the surfactant-rich phase and then the analytes were transferred into an alkaline solution with the help of ultrasound energy. The extracts were then analyzed by high-performance liquid chromatography (HPLC) coupled with a monolithic column. Several factors influencing the extraction efficiency were studied such as kind and concentration of surfactant, type and content of salts, kind and concentration of back extraction agent, and incubation temperature and time. Enrichment factors (EFs) were found in the range of 20⁻333 folds. The limits of detection of the studied neonicotinoids were in the range of 0.0003⁻0.002 µg mL −1 which are below the maximum residue limits (MRLs) established by the European Union (EU). Good repeatability was obtained with relative standard deviations lower than 1.92% and 4.54% for retention time ( t R ) and peak area, respectively. The developed extraction method was successfully applied for the analysis of water samples. No detectable residues of neonicotinoids in the studied samples were found.

Ion-pair cloud-point extraction: a new method for the determination of water-soluble vitamins in plasma and urine.

PubMed

Heydari, Rouhollah; Elyasi, Najmeh S

2014-10-01

A novel, simple, and effective ion-pair cloud-point extraction coupled with a gradient high-performance liquid chromatography method was developed for determination of thiamine (vitamin B1 ), niacinamide (vitamin B3 ), pyridoxine (vitamin B6 ), and riboflavin (vitamin B2 ) in plasma and urine samples. The extraction and separation of vitamins were achieved based on an ion-pair formation approach between these ionizable analytes and 1-heptanesulfonic acid sodium salt as an ion-pairing agent. Influential variables on the ion-pair cloud-point extraction efficiency, such as the ion-pairing agent concentration, ionic strength, pH, volume of Triton X-100, extraction temperature, and incubation time have been fully evaluated and optimized. Water-soluble vitamins were successfully extracted by 1-heptanesulfonic acid sodium salt (0.2% w/v) as ion-pairing agent with Triton X-100 (4% w/v) as surfactant phase at 50°C for 10 min. The calibration curves showed good linearity (r(2) > 0.9916) and precision in the concentration ranges of 1-50 μg/mL for thiamine and niacinamide, 5-100 μg/mL for pyridoxine, and 0.5-20 μg/mL for riboflavin. The recoveries were in the range of 78.0-88.0% with relative standard deviations ranging from 6.2 to 8.2%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cloud Impacts on Pavement Temperature in Energy Balance Models

NASA Astrophysics Data System (ADS)

Walker, C. L.

2013-12-01

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

Fog as an ecosystem service: Quantifying fog-mediated reductions in maximum temperature across coastal to inland transects in northern California

NASA Astrophysics Data System (ADS)

Torregrosa, A.; Flint, L. E.; Flint, A. L.; Combs, C.; Peters, J.

2013-12-01

Several studies have documented the human benefits of temperature cooling derived from coastal fog such as the reduction in the number of hospital visits/emergency response requests from heat stress-vulnerable population sectors or decreased energy consumption during periods when summer maximum temperatures are lower than normal. In this study we quantify the hourly, daily, monthly and seasonal thermal effect of fog and low clouds (FLC) hours on maximum summer temperatures across a northern California landscape. The FLC data summaries are calculated from the CIRA (Cooperative Institute for Research in the Atmosphere) 10 year archive that were derived from hourly night and day images using channels 1 (Visible), 2 (3.6 μm) and 4 (10.7 μm) NOAA GOES (Geostationary Operational Environmental Satellite). The FLC summaries were analyzed with two sets of site based data, meteorological (met) station-based measurements and downscaled interpolated PRISM data for selected point locations spanning a range of coastal to inland geographic conditions and met station locations. In addition to finding a 0.4 degree C per hour of FLC effect, our results suggest variability related to site specific thermal response. For example, sites closest to the coast have less thermal variability between low cloud and sunny days than sites further from the coast suggesting a much stronger influence of ocean temperature than of FLC thermal dynamics. The thermal relief provided by summertime FLC is equivalent in magnitude to the temperature increase projected by the driest and hottest of regional downscaled climate models using the A2 ('worst') IPCC scenario. Extrapolating these thermal calculations can facilitate future quantifications of the ecosystem service provided by summertime low clouds and fog.

Object Detection using the Kinect

DTIC Science & Technology

2012-03-01

Kinect camera and point cloud data from the Kinect’s structured light stereo system (figure 1). We obtain reasonable results using a single prototype...same manner we present in this report. For example, at Willow Garage , Steder uses a 3-D feature he developed to classify objects directly from point...detecting backpacks using the data available from the Kinect sensor. 4 3.1 Point Cloud Filtering Dense point clouds derived from stereo are notoriously

Tunnel Point Cloud Filtering Method Based on Elliptic Cylindrical Model

NASA Astrophysics Data System (ADS)

Zhua, Ningning; Jiaa, Yonghong; Luo, Lun

2016-06-01

The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points), therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

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.

Controlled generation of large volumes of atmospheric clouds in a ground-based environmental chamber

NASA Technical Reports Server (NTRS)

Hettel, H. J.; Depena, R. G.; Pena, J. A.

1975-01-01

Atmospheric clouds were generated in a 23,000 cubic meter environmental chamber as the first step in a two part study on the effects of contaminants on cloud formation. The generation procedure was modeled on the terrestrial generation mechanism so that naturally occurring microphysics mechanisms were operative in the cloud generation process. Temperature, altitude, liquid water content, and convective updraft velocity could be selected independently over the range of terrestrially realizable clouds. To provide cloud stability, a cotton muslin cylinder 29.3 meters in diameter and 24.2 meters high was erected within the chamber and continuously wetted with water at precisely the same temperature as the cloud. The improved instrumentation which permitted fast, precise, and continual measurements of cloud temperature and liquid water content is described.

A Modular Approach to Video Designation of Manipulation Targets for Manipulators

DTIC Science & Technology

2014-05-12

side view of a ray going through a point cloud of a water bottle sitting on the ground. The bottom left image shows the same point cloud after it has...System (ROS), Point Cloud Library (PCL), and OpenRAVE were used to a great extent to help promote reusability of the code developed during this

Venus atmosphere from Venus Express

NASA Astrophysics Data System (ADS)

Titov, Dmitri; Taylor, Fredric W.; Svedhem, Håkan; Titov, D.; Svedhem, H.; Taylor, F. W.; Bertaux, J.-L.; Drossart, P.; Haeusler, B.; Korablev, O. I.; Markiewicz, W. J.; Paetzold, M.; Piccioni, G.; Vandaele, A.-C.

Since April 2006 Venus Express has been performing a global survey of the remarkably dense, cloudy, and dynamic atmosphere of our near neighbour. A consistent picture of the climate on Venus is emerging on the basis of the new data on the global temperature structure, the com-position and its variations, the cloud morphology at various levels, the atmospheric dynamics and general circulation, and near-infrared emissions from trace species such as oxygen in the mesosphere. Vertical profiles of atmospheric temperature in the mesosphere and upper tropo-sphere show strong variability correlated with changes in the cloud top structure and many fine details indicating dynamical processes. Temperature sounding also shows that the main cloud deck at 50-60 km is convectively unstable over large portion of the planet, in agreement with the analysis of UV images. Imaging also reveals strong latitudinal variations and significant temporal changes in the global cloud top morphology, which will inevitably modulate the solar energy deposited in the atmosphere. The cloud top altitude varies from 72 km in the low and middle latitudes to 64 km in the polar region, marking vast polar depressions that form as a re-sult of the Hadley-type meridional circulation. Stellar and solar occultation measurements have revealed an extended upper haze of submicron particles and provided information on its optical properties. Solar occultation observations and deep atmosphere spectroscopy have quantified the distribution of the major trace gases H2O, SO2, CO, COS above and below the clouds, and so provided important input and validation for models of chemical cycles and dynamical trans-port. Cloud motion monitoring has characterised the mean state of the atmospheric circulation as well as its variability. Low and middle latitudes show an almost constant zonal wind speed of 100+/-20 m/s at the cloud tops and vertical wind shear of 2-3 m/s/km. Towards the pole, the wind speed drops quickly and the vertical shear vanishes. The meridional poleward wind ranges from 0 to about 15 m/s and there is some indication that it may change its direction at high latitudes. Comparison of the thermal wind field derived from temperature sounding to the cloud tracked winds confirms the approximate validity of cyclostrophic balance, at least in the latitude range from 30 S to 70 S. Maps of the non-LTE infrared emissions in the lines of O2, NO, CO2, OH originating near the mesopause at 95-105 km altitude show that the airglow peak intensity occurs close to the anti-solar point and its location depends on species. These observations promise significant improvement of thermospheric circulation models.

Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone

NASA Astrophysics Data System (ADS)

Xia, G.; Hu, C.

2018-04-01

The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.

Use of the X-Band Radar to Support the Detection of In-Flight Icing Hazards by the NASA Icing Remote Sensing System

NASA Technical Reports Server (NTRS)

Serke, David J.; Politovich, Marcia K.; Reehorst, Andrew L.; Gaydos, Andrew

2009-01-01

The Alliance Icing Research Study-II (AIRS-II) field program was conducted near Montreal, Canada during the winter of 2003. The NASA Icing Remote Detection System (NIRSS) was deployed to detect in-flight icing hazards and consisted of a vertically pointing multichannel radiometer, a ceilometer and an x-band cloud radar. The radiometer was used to derive atmospheric temperature soundings and integrated liquid water, while the ceilometer and radar were used only to define cloud boundaries. The purpose of this study is to show that the radar reflectivity profiles from AIRS-II case studies could be used to provide a qualitative icing hazard.

Tethered Balloon Operations at ARM AMF3 Site at Oliktok Point, AK

NASA Astrophysics Data System (ADS)

Dexheimer, D.; Lucero, D. A.; Helsel, F.; Hardesty, J.; Ivey, M.

2015-12-01

Oliktok Point has been the home of the Atmospheric Radiation Measurement Program's (ARM) third ARM Mobile Facility, or AMF3, since October 2013. The AMF3 is operated through Sandia National Laboratories and hosts instrumentation collecting continuous measurements of clouds, aerosols, precipitation, energy, and other meteorological variables. The Arctic region is warming more quickly than any other region due to climate change and Arctic sea ice is declining to record lows. Sparsity of atmospheric data from the Arctic leads to uncertainty in process comprehension, and atmospheric general circulation models (AGCM) are understood to underestimate low cloud presence in the Arctic. Increased vertical resolution of meteorological properties and cloud measurements will improve process understanding and help AGCMs better characterize Arctic clouds. SNL is developing a tethered balloon system capable of regular operation at AMF3 in order to provide increased vertical resolution atmospheric data. The tethered balloon can be operated within clouds at altitudes up to 7,000' AGL within DOE's R-2204 restricted area. Pressure, relative humidity, temperature, wind speed, and wind direction are recorded at multiple altitudes along the tether. These data were validated against stationary met tower data in Albuquerque, NM. The altitudes of the sensors were determined by GPS and calculated using a line counter and clinometer and compared. Wireless wetness sensors and supercooled liquid water content sensors have also been deployed and their data has been compared with other sensors. This presentation will provide an overview of the balloons, sensors, and test flights flown, and will provide a preliminary look at data from sensor validation campaigns and test flights.

Using LIDAR and UAV-derived point clouds to evaluate surface roughness in a gravel-bed braided river (Vénéon river, French Alps)

NASA Astrophysics Data System (ADS)

Vázquez Tarrío, Daniel; Borgniet, Laurent; Recking, Alain; Liebault, Frédéric; Vivier, Marie

2016-04-01

The present research is focused on the Vénéon river at Plan du Lac (Massif des Ecrins, France), an alpine braided gravel bed stream with a glacio-nival hydrological regime. It drains a catchment area of 316 km2. The present research is focused in a 2.5 km braided reach placed immediately upstream of a small hydropower dam. An airbone LIDAR survey was accomplished in October, 2014 by EDF (the company managing the small hydropower dam), and data coming from this LIDAR survey were available for the present research. Point density of the LIDAR-derived 3D-point cloud was between 20-50 points/m2, with a vertical precision of 2-3 cm over flat surfaces. Moreover, between April and Juin, 2015, we carried out a photogrammetrical campaign based in aerial images taken with an UAV-drone. The UAV-derived point-cloud has a point density of 200-300 points/m2, and a vertical precision over flat control surfaces comparable to that of the LIDAR point cloud (2-3 cm). Simultaneously to the UAV campaign, we took several Wolman samples with the aim of characterizing the grain size distribution of bed sediment. Wolman samples were taken following a geomorphological criterion (unit bars, head/tail of compound bars). Furthermore, some of the Wolman samples were repeated with the aim of defining the uncertainty of our sampling protocol. LIDAR and UAV-derived point clouds were treated in order to check whether both point-clouds were correctly co-aligned. After that, we estimated bed roughness using the detrended standard deviation of heights, in a 40-cm window. For all this data treatment we used CloudCompare. Then, we measured the distribution of roughness in the same geomorphological units where we took the Wolman samples, and we compared with the grain size distributions measured in the field: differences between UAV-point cloud roughness distributions and measured-grain size distribution (~1-2 cm) are in the same order of magnitude of the differences found between the repeated Wolman samples (~0.5-1.5 cm). Differences with LIDAR-derived roughness distributions are only slightly higher, which could be due to the lower point density of the LIDAR point clouds.

Regional distribution of the high-altitude clouds over the Indian subcontinent and surrounding oceanic regions based on seven years of satellite observations

NASA Astrophysics Data System (ADS)

Meenu, S.; Rajeev, K.; Parameswaran, K.; Suresh Raju, C.

2006-12-01

Quantitative estimates of the spatio-temporal variations in deep convective events over the Indian subcontinent, Arabian Sea, Bay of Bengal, and tropical Indian Ocean are carried out using the data obtained from Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-14 and NOAA-16 during the period 1996-2003. Pixels having thermal IR brightness temperature (BT) less than 245K are considered as high altitude clouds and those having BT<220 K are considered as very high altitude clouds. Very deep convective clouds are observed over north Bay of Bengal during the Asian summer monsoon season when the mean cloud top temperature reaches as low as 190K. Over the Head Bay of Bengal (HBoB) from June to September, more than 50% of the observed clouds are deep convective type and more than half of these deep convective clouds are very deep convective clouds. Histogram analysis of the cloud top temperatures during this period shows that over HBoB the most prominent cloud top temperature of the deep convective clouds is ~205K over the HBoB while that over southeast Arabian Sea (SEAS) is ~220K. This indicates that most probably the cloud top altitude over HBoB is ~2 km larger than that over SEAS during the Asian summer monsoon period. Another remarkable feature observed during the Asian summer monsoon period is the significantly low values of deep convective clouds observed over the south Bay of Bengal close to Srilanka, which appears as a large pool of reduced cloud amount surrounded by regions of large-scale deep convection. Over both SEAS and HBoB, the total, deep convective and very deep convective cloud amounts as well as their corresponding cloud top temperatures (or the altitude of the cloud top) undergo large seasonal variations, while such variations are less prominent over the eastern equatorial Indian Ocean.

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction

PubMed Central

Berveglieri, Adilson; Liang, Xinlian; Honkavaara, Eija

2017-01-01

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras. PMID:29207468

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction.

PubMed

Berveglieri, Adilson; Tommaselli, Antonio M G; Liang, Xinlian; Honkavaara, Eija

2017-12-02

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras.

Micellization and phase transitions in a triblock copolymer-D2O system

NASA Astrophysics Data System (ADS)

Odhner, Hosanna; Huff, Alison; Patton, Kelly; Jacobs, D. T.; Clover, Bryna; Greer, Sandra

2011-03-01

The triblock copolymer (``unimer'') of PPO-PEO-PPO (commercially known as 17R4) has hydrophobic ends and a hydrophilic center. When placed in D2 O at lower concentrations and temperatures, only a network of unimers exists. However, at higher concentrations or temperatures, micelles of different geometries can form. We have measured the micellization line marking the transition from only unimers to some micelles, as well as a one- to two-phase transition at higher temperatures. This second transition is an Ising-like, LCST critical point, based on the shape of the coexistence curve. We find the LCST to not correspond to the minimum of the cloud point curve, which indicates polydispersity as described by Sollich. We acknowledge the support from Research Corporation, NSF-REU grant DMR 0649112, The College of Wooster, and (for BC and SG) to the donors of the Petroleum Research Fund, administered by the American Chemical Society.

Validation of satellite-retrieved MBL cloud properties using DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, B.; Dong, X.; Minnis, P.; Sun-Mack, S.

2013-05-01

Marine Boundary Layer (MBL) cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) AMF AZORES site from June 2009 through December 2010. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS Ed4 cloud properties were averaged within a 30-km x 30-km box centered on the ARM AZORES site. Two datasets were analyzed: all of the single-layered unbroken decks (SL) and those cases without temperature inversions. The CERES-MODIS cloud top/base heights were determined from cloud top/base temperature by using a lapse rate method normalized to the 24-h mean surface air temperature. The preliminary results show: for all SL MBL at daytime, they are, on average, 0.148 km (cloud top) and 0.087 km (cloud base) higher than the ARM radar-lidar observed cloud top and base, respectively. At nighttime, they are 0.446 km (cloud top) and 0.334 km (cloud base). For those cases without temperature inversions, the comparisons are close to their SL counterparts. For cloud temperatures, the MODIS-derived cloud-top and -base temperatures are 1.6 K lower and 0.4 K higher than the surface values with correlations of 0.92 during daytime. At nighttime, the differences are slightly larger and correlations are lower than daytime comparisons. Variations in the height difference are mainly caused by uncertainties in the surface air temperatures and lapse rates. Based on a total of 61 daytime and 87 nighttime samples (ALL SL cases), the temperature inversion layers occur about 72% during daytime and 83% during nighttime. The difference of surface-observed lapse rate and the satellite derived lapse rate can be 1.6 K/km for daytime and 3.3K/km for nighttime. From these lapse rates, we can further analyze the surface air temperature difference that used to calculate these lapse rate, which are ~3K difference between surface-observed and the satellite derived during the daytime and 5.1 K during nighttime. Further studies of the cause of the temperature inversions that may help the cloud heights retrievals by satellite. The preliminary comparisons in MBL microphysical properties have shown that the averaged CERES-MODIS derived MBL cloud-droplet effective radius is only 1.5 μm larger than ARM retrieval (13.2 μm), and LWP values are also very close to each other (112 vs. 124 gm-2) with a relative large difference in optical depth (10.6 vs. 14.4).

Exploring noctilucent cloud variability using the nudged and extended version of the Canadian Middle Atmosphere Model

NASA Astrophysics Data System (ADS)

Kuilman, Maartje; Karlsson, Bodil; Benze, Susanne; Megner, Linda

2017-11-01

Ice particles in the summer mesosphere - such as those connected to noctilucent clouds and polar mesospheric summer echoes - have since their discovery contributed to the uncovering of atmospheric processes on various scales ranging from interactions on molecular levels to global scale circulation patterns. While there are numerous model studies on mesospheric ice microphysics and how the clouds relate to the background atmosphere, there are at this point few studies using comprehensive global climate models to investigate observed variability and climatology of noctilucent clouds. In this study it is explored to what extent the large-scale inter-annual characteristics of noctilucent clouds are captured in a 30-year run - extending from 1979 to 2009 - of the nudged and extended version of the Canadian Middle Atmosphere Model (CMAM30). To construct and investigate zonal mean inter-seasonal variability in noctilucent cloud occurrence frequency and ice mass density in both hemispheres, a simple cloud model is applied in which it is assumed that the ice content is solely controlled by the local temperature and water vapor volume mixing ratio. The model results are compared to satellite observations, each having an instrument-specific sensitivity when it comes to detecting noctilucent clouds. It is found that the model is able to capture the onset dates of the NLC seasons in both hemispheres as well as the hemispheric differences in NLCs, such as weaker NLCs in the SH than in the NH and differences in cloud height. We conclude that the observed cloud climatology and zonal mean variability are well captured by the model.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

Characterization of hydrometeors and precipitation over the Indian monsoon region using aircraft measurements

NASA Astrophysics Data System (ADS)

Maheskumar, R. S.; Padmakumari, B.; Konwar, Mahen; Morwal, S. B.; Deshpande, C. G.

2018-06-01

In-situ observations of cloud microphysical properties, carried out over different parts of Indian sub-continent using an instrumented research aircraft during Phase-I of Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) from June to September 2009, were studied. Different cloud probes were used to characterize the hydrometeor and precipitation types in the monsoon clouds. The results revealed that all liquid phase hydrometeors were present at temperatures -12 °C to 15 °C. Most of the presence of rain drops were found in the liquid water content (LWC) range from 0.5 to 2 g/m3. In general, rain drops are initiated when the droplet effective radius (Re) exceeded 12 μm. Rain dominated at the tops of young growing convective clouds even at temperatures colder than -10 °C. Mixed phase hydrometeors were present at temperatures from -2 °C to -18 °C. The cases where mixed phase precipitation occurred at temperatures warmer than about -7 °C were associated with influx of transported dust aerosol at the upper (supercooled) region of these cloud systems. Ice only hydrometeors were found at temperatures extending from -10 °C to -22 °C. Most of the monsoon rain is produced by warm and cold cloud/mixed-phase processes in the cloud. The combined Re from two different cloud probes is useful for validation of satellite derived cloud microphysical parameter.

FLASHFlux Info

Atmospheric Science Data Center

2013-05-20

... Surface Emissivity Cloud Area Fraction Cloud Effective Pressure Cloud Effective Temperature Cloud Effective Height Cloud Top Pressure Cloud Base Pressure Cloud Particle Phase Liquid Water Path Ice Water Path Water Particle Radius Ice Particle ...

Towards 3D Matching of Point Clouds Derived from Oblique and Nadir Airborne Imagery

NASA Astrophysics Data System (ADS)

Zhang, Ming

Because of the low-expense high-efficient image collection process and the rich 3D and texture information presented in the images, a combined use of 2D airborne nadir and oblique images to reconstruct 3D geometric scene has a promising market for future commercial usage like urban planning or first responders. The methodology introduced in this thesis provides a feasible way towards fully automated 3D city modeling from oblique and nadir airborne imagery. In this thesis, the difficulty of matching 2D images with large disparity is avoided by grouping the images first and applying the 3D registration afterward. The procedure starts with the extraction of point clouds using a modified version of the RIT 3D Extraction Workflow. Then the point clouds are refined by noise removal and surface smoothing processes. Since the point clouds extracted from different image groups use independent coordinate systems, there are translation, rotation and scale differences existing. To figure out these differences, 3D keypoints and their features are extracted. For each pair of point clouds, an initial alignment and a more accurate registration are applied in succession. The final transform matrix presents the parameters describing the translation, rotation and scale requirements. The methodology presented in the thesis has been shown to behave well for test data. The robustness of this method is discussed by adding artificial noise to the test data. For Pictometry oblique aerial imagery, the initial alignment provides a rough alignment result, which contains a larger offset compared to that of test data because of the low quality of the point clouds themselves, but it can be further refined through the final optimization. The accuracy of the final registration result is evaluated by comparing it to the result obtained from manual selection of matched points. Using the method introduced, point clouds extracted from different image groups could be combined with each other to build a more complete point cloud, or be used as a complement to existing point clouds extracted from other sources. This research will both improve the state of the art of 3D city modeling and inspire new ideas in related fields.

Fast Semantic Segmentation of 3d Point Clouds with Strongly Varying Density

NASA Astrophysics Data System (ADS)

Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

2016-06-01

We describe an effective and efficient method for point-wise semantic classification of 3D point clouds. The method can handle unstructured and inhomogeneous point clouds such as those derived from static terrestrial LiDAR or photogammetric reconstruction; and it is computationally efficient, making it possible to process point clouds with many millions of points in a matter of minutes. The key issue, both to cope with strong variations in point density and to bring down computation time, turns out to be careful handling of neighborhood relations. By choosing appropriate definitions of a point's (multi-scale) neighborhood, we obtain a feature set that is both expressive and fast to compute. We evaluate our classification method both on benchmark data from a mobile mapping platform and on a variety of large, terrestrial laser scans with greatly varying point density. The proposed feature set outperforms the state of the art with respect to per-point classification accuracy, while at the same time being much faster to compute.

A Microwave Technique for Mapping Ice Temperature in the Arctic Seasonal Sea Ice Zone

NASA Technical Reports Server (NTRS)

St.Germain, Karen M.; Cavalieri, Donald J.

1997-01-01

A technique for deriving ice temperature in the Arctic seasonal sea ice zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses ice concentration and type from a previously developed thin ice algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observations from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the ice temperature depends on ice type.

An ARM data-oriented diagnostics package to evaluate the climate model simulation

NASA Astrophysics Data System (ADS)

Zhang, C.; Xie, S.

2016-12-01

A set of diagnostics that utilize long-term high frequency measurements from the DOE Atmospheric Radiation Measurement (ARM) program is developed for evaluating the regional simulation of clouds, radiation and precipitation in climate models. The diagnostics results are computed and visualized automatically in a python-based package that aims to serve as an easy entry point for evaluating climate simulations using the ARM data, as well as the CMIP5 multi-model simulations. Basic performance metrics are computed to measure the accuracy of mean state and variability of simulated regional climate. The evaluated physical quantities include vertical profiles of clouds, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, radiative fluxes, aerosol and cloud microphysical properties. Process-oriented diagnostics focusing on individual cloud and precipitation-related phenomena are developed for the evaluation and development of specific model physical parameterizations. Application of the ARM diagnostics package will be presented in the AGU session. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, IM release number is: LLNL-ABS-698645.

A Voxel-Based Approach for Imaging Voids in Three-Dimensional Point Clouds

NASA Astrophysics Data System (ADS)

Salvaggio, Katie N.

Geographically accurate scene models have enormous potential beyond that of just simple visualizations in regard to automated scene generation. In recent years, thanks to ever increasing computational efficiencies, there has been significant growth in both the computer vision and photogrammetry communities pertaining to automatic scene reconstruction from multiple-view imagery. The result of these algorithms is a three-dimensional (3D) point cloud which can be used to derive a final model using surface reconstruction techniques. However, the fidelity of these point clouds has not been well studied, and voids often exist within the point cloud. Voids exist in texturally difficult areas, as well as areas where multiple views were not obtained during collection, constant occlusion existed due to collection angles or overlapping scene geometry, or in regions that failed to triangulate accurately. It may be possible to fill in small voids in the scene using surface reconstruction or hole-filling techniques, but this is not the case with larger more complex voids, and attempting to reconstruct them using only the knowledge of the incomplete point cloud is neither accurate nor aesthetically pleasing. A method is presented for identifying voids in point clouds by using a voxel-based approach to partition the 3D space. By using collection geometry and information derived from the point cloud, it is possible to detect unsampled voxels such that voids can be identified. This analysis takes into account the location of the camera and the 3D points themselves to capitalize on the idea of free space, such that voxels that lie on the ray between the camera and point are devoid of obstruction, as a clear line of sight is a necessary requirement for reconstruction. Using this approach, voxels are classified into three categories: occupied (contains points from the point cloud), free (rays from the camera to the point passed through the voxel), and unsampled (does not contain points and no rays passed through the area). Voids in the voxel space are manifested as unsampled voxels. A similar line-of-sight analysis can then be used to pinpoint locations at aircraft altitude at which the voids in the point clouds could theoretically be imaged. This work is based on the assumption that inclusion of more images of the void areas in the 3D reconstruction process will reduce the number of voids in the point cloud that were a result of lack of coverage. Voids resulting from texturally difficult areas will not benefit from more imagery in the reconstruction process, and thus are identified and removed prior to the determination of future potential imaging locations.

CERES-MISR Info

Atmospheric Science Data Center

2013-05-20

... Surface Albedo Cloud Area Fraction Cloud Effective Pressure Cloud Effective Temperature Cloud Effective Height Cloud Top Pressure Cloud Base Pressure Cloud Particle Phase Liquid Water Path Ice Water Path Water Particle Radius Ice Particle ...

CERES CRS Info

Atmospheric Science Data Center

2013-05-17

... Flux - Down Cloud Area Fraction Cloud Effective Pressure Cloud Effective Temperature Cloud Effective Height Cloud Top Pressure Cloud Base Pressure Cloud Particle Phase Liquid Water Path Ice Water Path Water Particle Radius Ice Particle ...

Impact of decadal cloud variations on the Earth’s energy budget

DOE PAGES

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

2016-10-31

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. We present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. Here, we find that cloud anomalies associated with these patterns significantly modify the Earth’s energy budget. Specifically, the decadal cloud feedback betweenmore » the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. Our results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and o er a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.« less

Impact of decadal cloud variations on the Earth’s energy budget

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

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. We present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. Here, we find that cloud anomalies associated with these patterns significantly modify the Earth’s energy budget. Specifically, the decadal cloud feedback betweenmore » the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. Our results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and o er a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.« less

Impact of decadal cloud variations on the Earth's energy budget

NASA Astrophysics Data System (ADS)

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

2016-12-01

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. Here we present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. We find that cloud anomalies associated with these patterns significantly modify the Earth's energy budget. Specifically, the decadal cloud feedback between the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. These results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and offer a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.

Classification by Using Multispectral Point Cloud Data

NASA Astrophysics Data System (ADS)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan

2015-04-01

Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.

Characterizing Sorghum Panicles using 3D Point Clouds

NASA Astrophysics Data System (ADS)

Lonesome, M.; Popescu, S. C.; Horne, D. W.; Pugh, N. A.; Rooney, W.

2017-12-01

To address demands of population growth and impacts of global climate change, plant breeders must increase crop yield through genetic improvement. However, plant phenotyping, the characterization of a plant's physical attributes, remains a primary bottleneck in modern crop improvement programs. 3D point clouds generated from terrestrial laser scanning (TLS) and unmanned aerial systems (UAS) based structure from motion (SfM) are a promising data source to increase the efficiency of screening plant material in breeding programs. This study develops and evaluates methods for characterizing sorghum (Sorghum bicolor) panicles (heads) in field plots from both TLS and UAS-based SfM point clouds. The TLS point cloud over experimental sorghum field at Texas A&M farm in Burleston County TX were collected using a FARO Focus X330 3D laser scanner. SfM point cloud was generated from UAS imagery captured using a Phantom 3 Professional UAS at 10m altitude and 85% image overlap. The panicle detection method applies point cloud reflectance, height and point density attributes characteristic of sorghum panicles to detect them and estimate their dimensions (panicle length and width) through image classification and clustering procedures. We compare the derived panicle counts and panicle sizes with field-based and manually digitized measurements in selected plots and study the strengths and limitations of each data source for sorghum panicle characterization.

Calibrating the HISA temperature: Measuring the temperature of the Riegel-Crutcher cloud

NASA Astrophysics Data System (ADS)

Dénes, H.; McClure-Griffiths, N. M.; Dickey, J. M.; Dawson, J. R.; Murray, C. E.

2018-06-01

H I self absorption (HISA) clouds are clumps of cold neutral hydrogen (H I) visible in front of warm background gas, which makes them ideal places to study the properties of the cold atomic component of the interstellar medium (ISM). The Riegel-Crutcher (R-C) cloud is the most striking HISA feature in the Galaxy. It is one of the closest HISA clouds to us and is located in the direction of the Galactic Centre, which provides a bright background. High-resolution interferometric measurements have revealed the filamentary structure of this cloud, however it is difficult to accurately determine the temperature and the density of the gas without optical depth measurements. In this paper we present new H I absorption observations with the Australia Telescope Compact Array (ATCA) against 46 continuum sources behind the Riegel-Crutcher cloud to directly measure the optical depth of the cloud. We decompose the complex H I absorption spectra into Gaussian components using an automated machine learning algorithm. We find 300 Gaussian components, from which 67 are associated with the R-C cloud (0 < vLSR < 10 km s-1, FWHM <10 km s-1). Combining the new H I absorption data with H I emission data from previous surveys we calculate the spin temperature and find it to be between 20 and 80 K. Our measurements uncover a temperature gradient across the cloud with spin temperatures decreasing towards positive Galactic latitudes. We also find three new OH absorption lines associated with the cloud, which support the presence of molecular gas.

Sensitivity of liquid clouds to homogenous freezing parameterizations.

PubMed

Herbert, Ross J; Murray, Benjamin J; Dobbie, Steven J; Koop, Thomas

2015-03-16

Water droplets in some clouds can supercool to temperatures where homogeneous ice nucleation becomes the dominant freezing mechanism. In many cloud resolving and mesoscale models, it is assumed that homogeneous ice nucleation in water droplets only occurs below some threshold temperature typically set at -40°C. However, laboratory measurements show that there is a finite rate of nucleation at warmer temperatures. In this study we use a parcel model with detailed microphysics to show that cloud properties can be sensitive to homogeneous ice nucleation as warm as -30°C. Thus, homogeneous ice nucleation may be more important for cloud development, precipitation rates, and key cloud radiative parameters than is often assumed. Furthermore, we show that cloud development is particularly sensitive to the temperature dependence of the nucleation rate. In order to better constrain the parameterization of homogeneous ice nucleation laboratory measurements are needed at both high (>-35°C) and low (<-38°C) temperatures. Homogeneous freezing may be significant as warm as -30°CHomogeneous freezing should not be represented by a threshold approximationThere is a need for an improved parameterization of homogeneous ice nucleation.

CERES SSF Current Info

Atmospheric Science Data Center

2013-05-17

... Surface Albedo Cloud Area Fraction Cloud Effective Pressure Cloud Effective Temperature Cloud Effective Height Cloud Top Pressure Cloud Base Pressure Cloud Particle Phase Liquid Water Path Ice Water Path Water Particle Radius Ice Particle ...

Efficient terrestrial laser scan segmentation exploiting data structure

NASA Astrophysics Data System (ADS)

Mahmoudabadi, Hamid; Olsen, Michael J.; Todorovic, Sinisa

2016-09-01

New technologies such as lidar enable the rapid collection of massive datasets to model a 3D scene as a point cloud. However, while hardware technology continues to advance, processing 3D point clouds into informative models remains complex and time consuming. A common approach to increase processing efficiently is to segment the point cloud into smaller sections. This paper proposes a novel approach for point cloud segmentation using computer vision algorithms to analyze panoramic representations of individual laser scans. These panoramas can be quickly created using an inherent neighborhood structure that is established during the scanning process, which scans at fixed angular increments in a cylindrical or spherical coordinate system. In the proposed approach, a selected image segmentation algorithm is applied on several input layers exploiting this angular structure including laser intensity, range, normal vectors, and color information. These segments are then mapped back to the 3D point cloud so that modeling can be completed more efficiently. This approach does not depend on pre-defined mathematical models and consequently setting parameters for them. Unlike common geometrical point cloud segmentation methods, the proposed method employs the colorimetric and intensity data as another source of information. The proposed algorithm is demonstrated on several datasets encompassing variety of scenes and objects. Results show a very high perceptual (visual) level of segmentation and thereby the feasibility of the proposed algorithm. The proposed method is also more efficient compared to Random Sample Consensus (RANSAC), which is a common approach for point cloud segmentation.

Three-dimensional reconstruction of indoor whole elements based on mobile LiDAR point cloud data

NASA Astrophysics Data System (ADS)

Gong, Yuejian; Mao, Wenbo; Bi, Jiantao; Ji, Wei; He, Zhanjun

2014-11-01

Ground-based LiDAR is one of the most effective city modeling tools at present, which has been widely used for three-dimensional reconstruction of outdoor objects. However, as for indoor objects, there are some technical bottlenecks due to lack of GPS signal. In this paper, based on the high-precision indoor point cloud data which was obtained by LiDAR, an international advanced indoor mobile measuring equipment, high -precision model was fulfilled for all indoor ancillary facilities. The point cloud data we employed also contain color feature, which is extracted by fusion with CCD images. Thus, it has both space geometric feature and spectral information which can be used for constructing objects' surface and restoring color and texture of the geometric model. Based on Autodesk CAD platform and with help of PointSence plug, three-dimensional reconstruction of indoor whole elements was realized. Specifically, Pointools Edit Pro was adopted to edit the point cloud, then different types of indoor point cloud data was processed, including data format conversion, outline extracting and texture mapping of the point cloud model. Finally, three-dimensional visualization of the real-world indoor was completed. Experiment results showed that high-precision 3D point cloud data obtained by indoor mobile measuring equipment can be used for indoor whole elements' 3-d reconstruction and that methods proposed in this paper can efficiently realize the 3 -d construction of indoor whole elements. Moreover, the modeling precision could be controlled within 5 cm, which was proved to be a satisfactory result.

Studying the influence of temperature and pressure on microphysical properties of mixed-phase clouds using airborne measurements

NASA Astrophysics Data System (ADS)

Andreea, Boscornea; Sabina, Stefan; Sorin-Nicolae, Vajaiac; Mihai, Cimpuieru

2015-04-01

One cloud type for which the formation and evolution process is not well-understood is the mixed-phase type. In general mixed-phase clouds consist of liquid droplets and ice crystals. The temperature interval within both liquid droplets and ice crystals can potentially coexist is limited to 0 °C and - 40 °C. Mixed-phase clouds account for 20% to 30% of the global cloud coverage. The need to understand the microphysical characteristics of mixed-phase clouds to improve numerical forecast modeling and radiative transfer calculation is of major interest in the atmospheric community. In the past, studies of cloud phase composition have been significantly limited by a lack of aircraft instruments capable of discriminating between the ice and liquid phase for a wide range of particle sizes. Presently, in situ airborne measurements provide the most accurate information about cloud microphysical characteristics. This information can be used for verification of both numerical models and cloud remote-sensing techniques. The knowledge of the temperature and pressure variation during the airborne measurements is crucial in order to understand their influence on the cloud dynamics and also their role in the cloud formation processes like accretion and coalescence. Therefore, in this paper is presented a comprehensive study of cloud microphysical properties in mixed-phase clouds in focus of the influence of temperature and pressure variation on both, cloud dynamics and the cloud formation processes, using measurements performed with the ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research in property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS). The airborne laboratory equipped for special research missions is based on a Hawker Beechcraft - King Air C90 GTx aircraft and is equipped with a sensors system CAPS - Cloud, Aerosol and Precipitation Spectrometer (30 bins, 0.51-50 µm) and a HAWKEYE cloud probe. The analyzed data in this work is acquired during 2 flight hours on the 23th of October 2014 in mixed clouds formations over Romania ( Craiova, Lat 44°19', Lon 23°48' ). The temperature variation during the cloud sounding was between -14 °C and -2 °C, with a maximum altitude in the cloud of 4863 m and a minimum altitude of 3353 m. In total 6 horizontal lines of 10 minutes each where performed recording ice crystal number concentrations (using the CIP - Cloud Imaging Probe) between 10 to 20 particles/cm3 outside the cloud layer and over 100 particles/cm3 inside the cloud layer and a number concentration of small droplets, aerosol and small ice crystals (using the CAS - Cloud Aerosol Spectrometer) between 150 particles/cm3 outside the cloud layer and 1600 particles/cm3 inside the cloud layer, this values confirms also the presence of IN (ice nuclei) in the atmosphere between the cloud layers. The results in respect with size distribution of cloud's particles and LWC show to be controlled by the temperature and pressure variations.

3D point cloud analysis of structured light registration in computer-assisted navigation in spinal surgeries

NASA Astrophysics Data System (ADS)

Gupta, Shaurya; Guha, Daipayan; Jakubovic, Raphael; Yang, Victor X. D.

2017-02-01

Computer-assisted navigation is used by surgeons in spine procedures to guide pedicle screws to improve placement accuracy and in some cases, to better visualize patient's underlying anatomy. Intraoperative registration is performed to establish a correlation between patient's anatomy and the pre/intra-operative image. Current algorithms rely on seeding points obtained directly from the exposed spinal surface to achieve clinically acceptable registration accuracy. Registration of these three dimensional surface point-clouds are prone to various systematic errors. The goal of this study was to evaluate the robustness of surgical navigation systems by looking at the relationship between the optical density of an acquired 3D point-cloud and the corresponding surgical navigation error. A retrospective review of a total of 48 registrations performed using an experimental structured light navigation system developed within our lab was conducted. For each registration, the number of points in the acquired point cloud was evaluated relative to whether the registration was acceptable, the corresponding system reported error and target registration error. It was demonstrated that the number of points in the point cloud neither correlates with the acceptance/rejection of a registration or the system reported error. However, a negative correlation was observed between the number of the points in the point-cloud and the corresponding sagittal angular error. Thus, system reported total registration points and accuracy are insufficient to gauge the accuracy of a navigation system and the operating surgeon must verify and validate registration based on anatomical landmarks prior to commencing surgery.

Study on Huizhou architecture of point cloud registration based on optimized ICP algorithm

NASA Astrophysics Data System (ADS)

Zhang, Runmei; Wu, Yulu; Zhang, Guangbin; Zhou, Wei; Tao, Yuqian

2018-03-01

In view of the current point cloud registration software has high hardware requirements, heavy workload and moltiple interactive definition, the source of software with better processing effect is not open, a two--step registration method based on normal vector distribution feature and coarse feature based iterative closest point (ICP) algorithm is proposed in this paper. This method combines fast point feature histogram (FPFH) algorithm, define the adjacency region of point cloud and the calculation model of the distribution of normal vectors, setting up the local coordinate system for each key point, and obtaining the transformation matrix to finish rough registration, the rough registration results of two stations are accurately registered by using the ICP algorithm. Experimental results show that, compared with the traditional ICP algorithm, the method used in this paper has obvious time and precision advantages for large amount of point clouds.

Homogeneous ice nucleation and supercooled liquid water in orographic wave clouds

NASA Technical Reports Server (NTRS)

Heymsfield, Andrew J.; Miloshevich, Larry M.

1993-01-01

This study investigates ice nucleation mechanisms in cold lenticular wave clouds, a cloud type characterized by quasi-steady-state air motions and microphysical properties. It is concluded that homogeneous ice nucleation is responsible for the ice production in these clouds at temperatures below about -33 C. The lack of ice nucleation observed above -33 C indicates a dearth of ice-forming nuclei, and hence heterogeneous ice nucleation, in these clouds. Aircraft measurements in the temperature range -31 to -41 C show the following complement of simultaneous and abrupt changes in cloud properties that indicate a transition from the liquid phase to ice: disappearance of liquid water; decrease in relative humidity from near water saturation to ice saturation; increase in mean particle size; change in particle concentration; and change in temperature due to the release of latent heat. A numerical model of cloud particle growth and homogeneous ice nucleation is used to aid in interpretation of our in situ measurements. The abrupt changes in observed cloud properties compare favorably, both qualitatively and quantitatively, with results from the homogeneous ice nucleation model. It is shown that the homogeneous ice nucleation rates from the measurements are consistent with the temperature-dependent rates employed by the model (within a factor of 100, corresponding to about 1 C in temperature) in the temperature range -35 deg to -38 C. Given the theoretical basis of the modeled rates, it may be reasonable to apply them throughout the -30 to -50 C temperature range considered by the theory.

Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets

NASA Astrophysics Data System (ADS)

Ge, Xuming

2017-08-01

The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

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

Effects of clouds on the Earth radiation budget; Seasonal and inter-annual patterns

NASA Technical Reports Server (NTRS)

Dhuria, Harbans L.

1992-01-01

Seasonal and regional variations of clouds and their effects on the climatological parameters were studied. The climatological parameters surface temperature, solar insulation, short-wave absorbed, long wave emitted, and net radiation were considered. The data of climatological parameters consisted of about 20 parameters of Earth radiation budget and clouds of 2070 target areas which covered the globe. It consisted of daily and monthly averages of each parameter for each target area for the period, Jun. 1979 - May 1980. Cloud forcing and black body temperature at the top of the atmosphere were calculated. Interactions of clouds, cloud forcing, black body temperature, and the climatological parameters were investigated and analyzed.

Object-Based Coregistration of Terrestrial Photogrammetric and ALS Point Clouds in Forested Areas

NASA Astrophysics Data System (ADS)

Polewski, P.; Erickson, A.; Yao, W.; Coops, N.; Krzystek, P.; Stilla, U.

2016-06-01

Airborne Laser Scanning (ALS) and terrestrial photogrammetry are methods applicable for mapping forested environments. While ground-based techniques provide valuable information about the forest understory, the measured point clouds are normally expressed in a local coordinate system, whose transformation into a georeferenced system requires additional effort. In contrast, ALS point clouds are usually georeferenced, yet the point density near the ground may be poor under dense overstory conditions. In this work, we propose to combine the strengths of the two data sources by co-registering the respective point clouds, thus enriching the georeferenced ALS point cloud with detailed understory information in a fully automatic manner. Due to markedly different sensor characteristics, coregistration methods which expect a high geometric similarity between keypoints are not suitable in this setting. Instead, our method focuses on the object (tree stem) level. We first calculate approximate stem positions in the terrestrial and ALS point clouds and construct, for each stem, a descriptor which quantifies the 2D and vertical distances to other stem centers (at ground height). Then, the similarities between all descriptor pairs from the two point clouds are calculated, and standard graph maximum matching techniques are employed to compute corresponding stem pairs (tiepoints). Finally, the tiepoint subset yielding the optimal rigid transformation between the terrestrial and ALS coordinate systems is determined. We test our method on simulated tree positions and a plot situated in the northern interior of the Coast Range in western Oregon, USA, using ALS data (76 x 121 m2) and a photogrammetric point cloud (33 x 35 m2) derived from terrestrial photographs taken with a handheld camera. Results on both simulated and real data show that the proposed stem descriptors are discriminative enough to derive good correspondences. Specifically, for the real plot data, 24 corresponding stems were coregistered with an average 2D position deviation of 66 cm.

Large-scale urban point cloud labeling and reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Liqiang; Li, Zhuqiang; Li, Anjian; Liu, Fangyu

2018-04-01

The large number of object categories and many overlapping or closely neighboring objects in large-scale urban scenes pose great challenges in point cloud classification. In this paper, a novel framework is proposed for classification and reconstruction of airborne laser scanning point cloud data. To label point clouds, we present a rectified linear units neural network named ReLu-NN where the rectified linear units (ReLu) instead of the traditional sigmoid are taken as the activation function in order to speed up the convergence. Since the features of the point cloud are sparse, we reduce the number of neurons by the dropout to avoid over-fitting of the training process. The set of feature descriptors for each 3D point is encoded through self-taught learning, and forms a discriminative feature representation which is taken as the input of the ReLu-NN. The segmented building points are consolidated through an edge-aware point set resampling algorithm, and then they are reconstructed into 3D lightweight models using the 2.5D contouring method (Zhou and Neumann, 2010). Compared with deep learning approaches, the ReLu-NN introduced can easily classify unorganized point clouds without rasterizing the data, and it does not need a large number of training samples. Most of the parameters in the network are learned, and thus the intensive parameter tuning cost is significantly reduced. Experimental results on various datasets demonstrate that the proposed framework achieves better performance than other related algorithms in terms of classification accuracy and reconstruction quality.

A study of surface temperatures, clouds and net radiation

NASA Technical Reports Server (NTRS)

Dhuria, Harbans

1994-01-01

The study is continuing and it is focused on examining seasonal relationships between climate parameters such as the surface temperatures, the net radiation and cloud types and amount on a global basis for the period February 1985 to January 1987. The study consists of an analysis of the combined Earth Radiation Budget Experiment (ERBE) and International Satellite Cloud Climatology Program (ISCCP) products. The main emphasis is on obtaining the information about the interactions and relationships of Earth Radiation Budget parameters, cloud and temperature information. The purpose is to gain additional qualitative and quantitative insight into the cloud climate relationship.

Tropical Storm Ernesto over Cuba

NASA Image and Video Library

2006-08-28

This infrared image shows Tropical Storm Ernesto over Cuba, from the Atmospheric Infrared Sounder AIRS on NASA Aqua satellite in August, 2006. Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red). http://photojournal.jpl.nasa.gov/catalog/PIA00510

Typhoon Ioke in the Western Pacific

NASA Image and Video Library

2006-08-29

This infrared image shows Typhoon Ioke in the Western Pacific, from the Atmospheric Infrared Sounder AIRS on NASA Aqua satellite in August, 2006. Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red). http://photojournal.jpl.nasa.gov/catalog/PIA00511

Hurricane Ileana in the Eastern Pacific

NASA Image and Video Library

2006-08-22

This is an infrared image of Hurricane Ileana in the Eastern Pacific, from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on August 22, 2006. This AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). http://photojournal.jpl.nasa.gov/catalog/PIA00509

Overview of the CERES Edition-4 Multilayer Cloud Property Datasets

NASA Astrophysics Data System (ADS)

Chang, F. L.; Minnis, P.; Sun-Mack, S.; Chen, Y.; Smith, R. A.; Brown, R. R.

2014-12-01

Knowledge of the cloud vertical distribution is important for understanding the role of clouds on earth's radiation budget and climate change. Since high-level cirrus clouds with low emission temperatures and small optical depths can provide a positive feedback to a climate system and low-level stratus clouds with high emission temperatures and large optical depths can provide a negative feedback effect, the retrieval of multilayer cloud properties using satellite observations, like Terra and Aqua MODIS, is critically important for a variety of cloud and climate applications. For the objective of the Clouds and the Earth's Radiant Energy System (CERES), new algorithms have been developed using Terra and Aqua MODIS data to allow separate retrievals of cirrus and stratus cloud properties when the two dominant cloud types are simultaneously present in a multilayer system. In this paper, we will present an overview of the new CERES Edition-4 multilayer cloud property datasets derived from Terra as well as Aqua. Assessment of the new CERES multilayer cloud datasets will include high-level cirrus and low-level stratus cloud heights, pressures, and temperatures as well as their optical depths, emissivities, and microphysical properties.

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.

Dynamical States of Low Temperature Cirrus

NASA Technical Reports Server (NTRS)

Barahona, D.; Nenes, A.

2011-01-01

Low ice crystal concentration and sustained in-cloud supersaturation, commonly found in cloud observations at low temperature, challenge our understanding of cirrus formation. Heterogeneous freezing from effloresced ammonium sulfate, glassy aerosol, dust and black carbon are proposed to cause these phenomena; this requires low updrafts for cirrus characteristics to agree with observations and is at odds with the gravity wave spectrum in the upper troposphere. Background temperature fluctuations however can establish a dynamical equilibrium between ice production and sedimentation loss (as opposed to ice crystal formation during the first stages of cloud evolution and subsequent slow cloud decay) that explains low temperature cirrus properties. This newly-discovered state is favored at low temperatures and does not require heterogeneous nucleation to occur (the presence of ice nuclei can however facilitate its onset). Our understanding of cirrus clouds and their role in anthropogenic climate change is reshaped, as the type of dynamical forcing will set these clouds in one of two preferred microphysical regimes with very different susceptibility to aerosol.

Prediction based proactive thermal virtual machine scheduling in green clouds.

PubMed

Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

2014-01-01

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

Impact of cloud timing on surface temperature and related hydroclimatic dynamics

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Yin, J.

2015-12-01

Cloud feedbacks have long been identified as one of the largest source of uncertainty in climate change predictions. Differences in the spatial distribution of clouds and the related impact on surface temperature and climate dynamics have been recently emphasized in quasi-equilibrium General Circulation Models (GCM). However, much less attention has been paid to the temporal variation of cloud presence and thickness. Clouds in fact shade the solar radiation during the daytime, but also acts as greenhouse gas to reduce the emission of longwave radiation to the outer space anytime of the day. Thus it is logical to expect that even small differences in timing and thickness of clouds could result in very different predictions in GCMs. In this study, these two effects of cloud dynamics are analyzed by tracking the cloud impacts on longwave and shortwave radiation in a minimalist transient thermal balance model of the land surface. The marked changes in surface temperature due to alterations in the timing of onset of clouds demonstrate that capturing temporal variation of cloud at sub-daily scale should be a priority in cloud parameterization schemes in GCMs.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Temperature characterisation of the CLOUD chamber at CERN

NASA Astrophysics Data System (ADS)

Dias, A. M.; Almeida, J.; Kirkby, J.; Mathot, S.; Onnela, A.; Vogel, A.; Ehrhart, S.

2014-12-01

Temperature stability, uniformity and absolute scale inside the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN are important for experiments on aerosol particle nucleation and ice/liquid cloud formation. In order to measure the air temperature, a comprehensive set of arrays ("strings") of platinum resistance thermometers, thermocouples and optical sensors have been installed inside the 26 m3 chamber. The thermal sensors must meet several challenging design requirements: ultra-clean materials, 0.01 K measurement sensitivity, high absolute precision (<0.1 K), 200 K - 373 K range, ability to operate in high electric fields (20 kV/m), and fast response in air (~1 s) in order to measure rapid changes of temperature during ice/liquid cloud formation in the chamber by adiabatic pressure reductions. This presentation will focus on the design of the thermometer strings and the thermal performance of the chamber during the CLOUD8 and CLOUD9 campaigns, 2013-2014, together with the planned upgrades of the CLOUD thermal system.

Thermodynamic control of anvil cloud amount

PubMed Central

Bony, Sandrine; Stevens, Bjorn; Coppin, David; Becker, Tobias; Reed, Kevin A.; Voigt, Aiko

2016-01-01

General circulation models show that as the surface temperature increases, the convective anvil clouds shrink. By analyzing radiative–convective equilibrium simulations, we show that this behavior is rooted in basic energetic and thermodynamic properties of the atmosphere: As the climate warms, the clouds rise and remain at nearly the same temperature, but find themselves in a more stable atmosphere; this enhanced stability reduces the convective outflow in the upper troposphere and decreases the anvil cloud fraction. By warming the troposphere and increasing the upper-tropospheric stability, the clustering of deep convection also reduces the convective outflow and the anvil cloud fraction. When clouds are radiatively active, this robust coupling between temperature, high clouds, and circulation exerts a positive feedback on convective aggregation and favors the maintenance of strongly aggregated atmospheric states at high temperatures. This stability iris mechanism likely contributes to the narrowing of rainy areas as the climate warms. Whether or not it influences climate sensitivity requires further investigation. PMID:27412863

Thermodynamic control of anvil cloud amount

DOE PAGES

Bony, Sandrine; Stevens, Bjorn; Coppin, David; ...

2016-07-13

General circulation models show that as the surface temperature increases, the convective anvil clouds shrink. By analyzing radiative–convective equilibrium simulations, our work shows that this behavior is rooted in basic energetic and thermodynamic properties of the atmosphere: As the climate warms, the clouds rise and remain at nearly the same temperature, but find themselves in a more stable atmosphere; this enhanced stability reduces the convective outflow in the upper troposphere and decreases the anvil cloud fraction. By warming the troposphere and increasing the upper-tropospheric stability, the clustering of deep convection also reduces the convective outflow and the anvil cloud fraction.more » When clouds are radiatively active, this robust coupling between temperature, high clouds, and circulation exerts a positive feedback on convective aggregation and favors the maintenance of strongly aggregated atmospheric states at high temperatures. This stability iris mechanism likely contributes to the narrowing of rainy areas as the climate warms. Whether or not it influences climate sensitivity requires further investigation.« less

Silicon chemistry in interstellar clouds

NASA Technical Reports Server (NTRS)

Langer, William D.; Glassgold, A. E.

1989-01-01

Interstellar SiO was discovered shortly after CO but it has been detected mainly in high density and high temperature regions associated with outflow sources. A new model of interstellar silicon chemistry that explains the lack of SiO detections in cold clouds is presented which contains an exponential temperature dependence for the SiO abundance. A key aspect of the model is the sensitivity of SiO production by neutral silicon reactions to density and temperature, which arises from the dependence of the rate coefficients on the population of the excited fine structure levels of the silicon atom. This effect was originally pointed out in the context of neutral reactions of carbon and oxygen by Graff, who noted that the leading term in neutral atom-molecule interactions involves the quadrupole moment of the atom. Similar to the case of carbon, the requirement that Si has a quadrupole moment requires population of the J = 1 level, which lies 111K above the J = 0 ground state and has a critical density n(cr) equal to or greater than 10(6)/cu cm. The SiO abundance then has a temperature dependence proportional to exp(-111/T) and a quadratic density dependence for n less than n(cr). As part of the explanation of the lack of SiO detections at low temperatures and densities, this model also emphasizes the small efficiencies of the production routes and the correspondingly long times needed to reach equilibrium. Measurements of the abundance of SiO, in conjunction with theory, can provide information on the physical properties of interstellar clouds such as the abundances of oxygen bearing molecules and the depletion of interstellar silicon.

Physical Processes in Coastal Stratocumulus Clouds from Aircraft Measurements During UPPEF 2012

DTIC Science & Technology

2013-09-01

pressure, dew point, water vapor, absolute humidity, and carbon dioxide concentration. There were various upward and downward looking pyranometers ...Meteorological parameters IR Temperature -50 to +20 °C Up-looking modified Kipp & Zonen CM-22 pyranometer (CIRPAS/NRL) Meteorological parameters Down...welling Solar Irradiance 0-1400 W m -2 Down-looking modified Kipp & Zonen CM-22 pyranometer (CIRPAS/NRL) Meteorological parameters Up-welling Solar

ARM Tethered Balloon System & AALCO Activities at AMF3 Site at Oliktok Point, AK

NASA Astrophysics Data System (ADS)

Hardesty, J.; Dexheimer, D.; Mei, F.; Roesler, E. L.; Longbottom, C.; Hillman, B. R.

2017-12-01

Sandia National Laboratories (SNL) has operated the Atmospheric Radiation Measurement program's (ARM) third ARM Mobile Facility (AMF3) and the restricted airspace associated with it at Oliktok Point, Alaska, since October 2013. The site hosts ground-based instrumentation which collects a variety of continuous atmospheric measurements as well as user-conducted unmanned aircraft and tethered balloon campaigns. SNL has operated ARM's tethered balloon system (TBS) as part of the Inaugural Campaigns for ARM Research using Unmanned Systems (ICARUS) since 2016. AALCO (Aerial Assessment of Liquid in Clouds at Oliktok), is an ARM Intensive Operations Period conducted by SNL at the AMF3 since 2016. The operation of the TBS during ICARUS and AALCO to altitudes above 4,000' AGL in a variety of seasons and conditions is addressed. A Distributed Temperature Sensing (DTS) system and supercooled liquid water content (SLWC) sensors have been deployed under both campaigns. The performance of these sensors is discussed and results are presented. DTS measurements and their relationship to concurrent temperature measurements from unmanned aircraft and radiosondes are shown. SLWC sensor in situ measurements are compared with microwave radiometer and radiosonde-derived measurements. Preliminary analysis of using Large Eddy Simulations to compare with the SLWC measurements reveals three-dimensional properties of the observed clouds.

Superposition and alignment of labeled point clouds.

PubMed

Fober, Thomas; Glinca, Serghei; Klebe, Gerhard; Hüllermeier, Eyke

2011-01-01

Geometric objects are often represented approximately in terms of a finite set of points in three-dimensional euclidean space. In this paper, we extend this representation to what we call labeled point clouds. A labeled point cloud is a finite set of points, where each point is not only associated with a position in three-dimensional space, but also with a discrete class label that represents a specific property. This type of model is especially suitable for modeling biomolecules such as proteins and protein binding sites, where a label may represent an atom type or a physico-chemical property. Proceeding from this representation, we address the question of how to compare two labeled points clouds in terms of their similarity. Using fuzzy modeling techniques, we develop a suitable similarity measure as well as an efficient evolutionary algorithm to compute it. Moreover, we consider the problem of establishing an alignment of the structures in the sense of a one-to-one correspondence between their basic constituents. From a biological point of view, alignments of this kind are of great interest, since mutually corresponding molecular constituents offer important information about evolution and heredity, and can also serve as a means to explain a degree of similarity. In this paper, we therefore develop a method for computing pairwise or multiple alignments of labeled point clouds. To this end, we proceed from an optimal superposition of the corresponding point clouds and construct an alignment which is as much as possible in agreement with the neighborhood structure established by this superposition. We apply our methods to the structural analysis of protein binding sites.

Automatic registration of terrestrial point clouds based on panoramic reflectance images and efficient BaySAC

NASA Astrophysics Data System (ADS)

Kang, Zhizhong

2013-10-01

This paper presents a new approach to automatic registration of terrestrial laser scanning (TLS) point clouds utilizing a novel robust estimation method by an efficient BaySAC (BAYes SAmpling Consensus). The proposed method directly generates reflectance images from 3D point clouds, and then using SIFT algorithm extracts keypoints to identify corresponding image points. The 3D corresponding points, from which transformation parameters between point clouds are computed, are acquired by mapping the 2D ones onto the point cloud. To remove false accepted correspondences, we implement a conditional sampling method to select the n data points with the highest inlier probabilities as a hypothesis set and update the inlier probabilities of each data point using simplified Bayes' rule for the purpose of improving the computation efficiency. The prior probability is estimated by the verification of the distance invariance between correspondences. The proposed approach is tested on four data sets acquired by three different scanners. The results show that, comparing with the performance of RANSAC, BaySAC leads to less iterations and cheaper computation cost when the hypothesis set is contaminated with more outliers. The registration results also indicate that, the proposed algorithm can achieve high registration accuracy on all experimental datasets.

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

Bony, Sandrine; Stevens, Bjorn; Coppin, David

General circulation models show that as the surface temperature increases, the convective anvil clouds shrink. By analyzing radiative–convective equilibrium simulations, our work shows that this behavior is rooted in basic energetic and thermodynamic properties of the atmosphere: As the climate warms, the clouds rise and remain at nearly the same temperature, but find themselves in a more stable atmosphere; this enhanced stability reduces the convective outflow in the upper troposphere and decreases the anvil cloud fraction. By warming the troposphere and increasing the upper-tropospheric stability, the clustering of deep convection also reduces the convective outflow and the anvil cloud fraction.more » When clouds are radiatively active, this robust coupling between temperature, high clouds, and circulation exerts a positive feedback on convective aggregation and favors the maintenance of strongly aggregated atmospheric states at high temperatures. This stability iris mechanism likely contributes to the narrowing of rainy areas as the climate warms. Whether or not it influences climate sensitivity requires further investigation.« less

Skylab near-infrared observations of clouds indicating supercooled liquid water droplets

NASA Technical Reports Server (NTRS)

Curran, R. J.; Wu, M.-L. C.

1982-01-01

Orographically-induced lee-wave clouds were observed over New Mexico by a multichannel scanning radiometer on Skylab during December 1973. Channels centered at 0.83, 1.61 and 2.125 microns were used to determine the cloud optical thickness, thermodynamic phase and effective particle size. An additional channel centered at 11.4 microns was used to determine cloud-top temperature, which was corroborated through comparison with the stereographically determined cloud top altitudes and conventional temperature soundings. Analysis of the measured near-infrared reflection functions at 1.61 and 2.125 microns are most easily interpreted as indicating the presence of liquid-phase water droplets. This interpretation is not conclusive even after considerable effort to understand possible sources for misinterpretation. However, if accepted the resulting phase determination is considered anomalous due to the inferred cloud-top temperatures being in the -32 to -47 C range. Theory for the homogeneous nucleation of pure supercooled liquid water droplets predicts very short lifetimes for the liquid phase at these cold temperatures. A possible explanation for the observations is that the wave-clouds are composed of solution droplets. Impurities in the cloud droplets could decrease the homogeneous freezing rate for these droplets, permitting them to exist for a longer time in the liquid phase, at the cold temperatures found.

A CloudSat-CALIPSO View of Cloud and Precipitation Properties Across Cold Fronts over the Global Oceans

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.

2015-01-01

The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the post frontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime post frontal precipitation.

Autumn at Titan's South Pole: The 220 cm-1 Cloud

NASA Astrophysics Data System (ADS)

Jennings, D. E.; Cottini, V.; Achterberg, R. K.; Anderson, C. M.; Flasar, F. M.; de Kok, R. J.; Teanby, N. A.; Coustenis, A.; Vinatier, S.

2015-10-01

Beginning in 2012 an atmospheric cloud known by its far-infrared emission has formed rapidly at Tit an's South Pole [1, 2]. The build-up of this condensate is a result of deepening temperatures and a gathering of gases as Winter approaches. Emission from the cloud in the south has been doubling each year since 2012, in contrast to the north where it has halved every 3.8 years since 2004. The morphology of the cloud in the south is quite different from that in the north. In the north, the cloud has extended over the whole polar region beyond 55 N, whereas in the south the cloud has been confined to within about 10 degrees of the pole. The cloud in the north has had the form of a uniform hood, whereas the southern cloud has been much more complex. A map from December 2014,recorded by the Composite Infrared Spectrometer (CIRS) on Cassini, showed the 220 cm-1 emission coming from a distinct ring with a maximum at about 80 S. In contrast, emissions from the gases HC3N, C4H2 and C6H6 peaked near the pole and had a ring at 70 S. The 220 cm-1 ring at 80 S coincided with the minimum in the gas emission pattern. The80 S condensate ring encompassed the vortex cloud seen by the Cassini Imaging Science Subsystem (ISS) and Visible and Infrared Mapping Spectrometer (VIMS)[3, 4]. Both the 220 cm-1 ring and the gas "bull's-eye" pattern were centered on a point that was shifted from the geographic South Pole by 4 degrees in the direction of the Sun. This corresponds to the overall tilt of Titan's atmosphere discovered from temperature maps early in the Cassini mission by Achterberg et al. [5]. The tilt may be reinforced by the presumably twice-yearly (north and south) spin-up of the atmosphere at the autumnal pole. The bull's-eye pattern of the gas emissions can be explained by the retrieved abundance distributions, which are maximum near the pole and decrease sharply toward lower latitudes, together with temperatures that are minimum at the pole and increase toward lower latitudes. The increasing temperatures overcome the decreasing gas abundances to produce emission in the narrow range around 70 S. This cannot, however, explain the maximum of emission at 80 S from the condensate ring. The coincidence at 80 S of the 220 cm-1 peak with the gas emission minimum may indicate where the condensation is taking place. The central, polar minimum in the cloud emission may be due to faster rain-out and smaller extinction cross-sections. Spectral maps from 2013-15 [6] show that the gas emission pattern has been evolving quickly, with noticeable changes from one flyby to the next (about one month). The bull's-eye structure appears to have been most prominent in early 2014 and by late 2014 the pattern was becoming more uniform. As Titan progresses through late southern Autumn we expect the morphology of the condensate cloud to take on a hood-like distribution similar to that in the north.

Continuum Limit of Total Variation on Point Clouds

NASA Astrophysics Data System (ADS)

García Trillos, Nicolás; Slepčev, Dejan

2016-04-01

We consider point clouds obtained as random samples of a measure on a Euclidean domain. A graph representing the point cloud is obtained by assigning weights to edges based on the distance between the points they connect. Our goal is to develop mathematical tools needed to study the consistency, as the number of available data points increases, of graph-based machine learning algorithms for tasks such as clustering. In particular, we study when the cut capacity, and more generally total variation, on these graphs is a good approximation of the perimeter (total variation) in the continuum setting. We address this question in the setting of Γ-convergence. We obtain almost optimal conditions on the scaling, as the number of points increases, of the size of the neighborhood over which the points are connected by an edge for the Γ-convergence to hold. Taking of the limit is enabled by a transportation based metric which allows us to suitably compare functionals defined on different point clouds.

Point cloud registration from local feature correspondences-Evaluation on challenging datasets.

PubMed

Petricek, Tomas; Svoboda, Tomas

2017-01-01

Registration of laser scans, or point clouds in general, is a crucial step of localization and mapping with mobile robots or in object modeling pipelines. A coarse alignment of the point clouds is generally needed before applying local methods such as the Iterative Closest Point (ICP) algorithm. We propose a feature-based approach to point cloud registration and evaluate the proposed method and its individual components on challenging real-world datasets. For a moderate overlap between the laser scans, the method provides a superior registration accuracy compared to state-of-the-art methods including Generalized ICP, 3D Normal-Distribution Transform, Fast Point-Feature Histograms, and 4-Points Congruent Sets. Compared to the surface normals, the points as the underlying features yield higher performance in both keypoint detection and establishing local reference frames. Moreover, sign disambiguation of the basis vectors proves to be an important aspect in creating repeatable local reference frames. A novel method for sign disambiguation is proposed which yields highly repeatable reference frames.

Identification Code of Interstellar Cloud within IRAF

NASA Astrophysics Data System (ADS)

Lee, Youngung; Jung, Jae Hoon; Kim, Hyun-Goo

1997-12-01

We present a code which identifies individual clouds in crowded region using IMFORT interface within Image Reduction and Analysis Facility(IRAF). We define a cloud as an object composed of all pixels in longitude, latitude, and velocity that are simply connected and that lie above some threshold temperature. The code searches the whole pixels of the data cube in efficient way to isolate individual clouds. Along with identification of clouds it is designed to estimate their mean values of longitudes, latitudes, and velocities. In addition, a function of generating individual images(or cube data) of identified clouds is added up. We also present identified individual clouds using a 12CO survey data cube of Galactic Anticenter Region(Lee et al. 1997) as a test example. We used a threshold temperature of 5 sigma rms noise level of the data. With a higher threshold temperature, we isolated subclouds of a huge cloud identified originally. As the most important parameter to identify clouds is the threshold value, its effect to the size and velocity dispersion is discussed rigorously.

On the performance of metrics to predict quality in point cloud representations

NASA Astrophysics Data System (ADS)

Alexiou, Evangelos; Ebrahimi, Touradj

2017-09-01

Point clouds are a promising alternative for immersive representation of visual contents. Recently, an increased interest has been observed in the acquisition, processing and rendering of this modality. Although subjective and objective evaluations are critical in order to assess the visual quality of media content, they still remain open problems for point cloud representation. In this paper we focus our efforts on subjective quality assessment of point cloud geometry, subject to typical types of impairments such as noise corruption and compression-like distortions. In particular, we propose a subjective methodology that is closer to real-life scenarios of point cloud visualization. The performance of the state-of-the-art objective metrics is assessed by considering the subjective scores as the ground truth. Moreover, we investigate the impact of adopting different test methodologies by comparing them. Advantages and drawbacks of every approach are reported, based on statistical analysis. The results and conclusions of this work provide useful insights that could be considered in future experimentation.

Semantic Segmentation of Building Elements Using Point Cloud Hashing

NASA Astrophysics Data System (ADS)

Chizhova, M.; Gurianov, A.; Hess, M.; Luhmann, T.; Brunn, A.; Stilla, U.

2018-05-01

For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect) into different building types and structural elements (dome, nave, transept etc.), including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling).

Comparison of Uas-Based Photogrammetry Software for 3d Point Cloud Generation: a Survey Over a Historical Site

NASA Astrophysics Data System (ADS)

Alidoost, F.; Arefi, H.

2017-11-01

Nowadays, Unmanned Aerial System (UAS)-based photogrammetry offers an affordable, fast and effective approach to real-time acquisition of high resolution geospatial information and automatic 3D modelling of objects for numerous applications such as topography mapping, 3D city modelling, orthophoto generation, and cultural heritages preservation. In this paper, the capability of four different state-of-the-art software packages as 3DSurvey, Agisoft Photoscan, Pix4Dmapper Pro and SURE is examined to generate high density point cloud as well as a Digital Surface Model (DSM) over a historical site. The main steps of this study are including: image acquisition, point cloud generation, and accuracy assessment. The overlapping images are first captured using a quadcopter and next are processed by different software to generate point clouds and DSMs. In order to evaluate the accuracy and quality of point clouds and DSMs, both visual and geometric assessments are carry out and the comparison results are reported.

Multiview point clouds denoising based on interference elimination

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Feature-based three-dimensional registration for repetitive geometry in machine vision

PubMed Central

Gong, Yuanzheng; Seibel, Eric J.

2016-01-01

As an important step in three-dimensional (3D) machine vision, 3D registration is a process of aligning two or multiple 3D point clouds that are collected from different perspectives together into a complete one. The most popular approach to register point clouds is to minimize the difference between these point clouds iteratively by Iterative Closest Point (ICP) algorithm. However, ICP does not work well for repetitive geometries. To solve this problem, a feature-based 3D registration algorithm is proposed to align the point clouds that are generated by vision-based 3D reconstruction. By utilizing texture information of the object and the robustness of image features, 3D correspondences can be retrieved so that the 3D registration of two point clouds is to solve a rigid transformation. The comparison of our method and different ICP algorithms demonstrates that our proposed algorithm is more accurate, efficient and robust for repetitive geometry registration. Moreover, this method can also be used to solve high depth uncertainty problem caused by little camera baseline in vision-based 3D reconstruction. PMID:28286703

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.

An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

NASA Astrophysics Data System (ADS)

Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

2018-03-01

Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

Incorporation of a Cumulus Fraction Scheme in the GRAPES_Meso and Evaluation of Its Performance

NASA Astrophysics Data System (ADS)

Zheng, X.

2016-12-01

Accurate simulation of cloud cover fraction is a key and difficult issue in numerical modeling studies. Preliminary evaluations have indicated that cloud fraction is generally underestimated in GRAPES_Meso simulations, while the cloud fraction scheme (CFS) of ECMWF can provide more realistic results. Therefore, the ECMWF cumulus fraction scheme is introduced into GRAPES_Meso to replace the original CFS, and the model performance with the new CFS is evaluated based on simulated three-dimensional cloud fractions and surface temperature. Results indicate that the simulated cloud fractions increase and become more accurate with the new CFS; the simulation for vertical cloud structure has improved too; errors in surface temperature simulation have decreased. The above analysis and results suggest that the new CFS has a positive impact on cloud fraction and surface temperature simulation.

Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction

NASA Astrophysics Data System (ADS)

Díaz-Vilariño, L.; Verbree, E.; Zlatanova, S.; Diakité, A.

2017-09-01

Updated and detailed indoor models are being increasingly demanded for various applications such as emergency management or navigational assistance. The consolidation of new portable and mobile acquisition systems has led to a higher availability of 3D point cloud data from indoors. In this work, we explore the combined use of point clouds and trajectories from SLAM-based laser scanner to automate the reconstruction of building indoors. The methodology starts by door detection, since doors represent transitions from one indoor space to other, which constitutes an initial approach about the global configuration of the point cloud into building rooms. For this purpose, the trajectory is used to create a vertical point cloud profile in which doors are detected as local minimum of vertical distances. As point cloud and trajectory are related by time stamp, this feature is used to subdivide the point cloud into subspaces according to the location of the doors. The correspondence between subspaces and building rooms is not unambiguous. One subspace always corresponds to one room, but one room is not necessarily depicted by just one subspace, for example, in case of a room containing several doors and in which the acquisition is performed in a discontinue way. The labelling problem is formulated as combinatorial approach solved as a minimum energy optimization. Once the point cloud is subdivided into building rooms, envelop (conformed by walls, ceilings and floors) is reconstructed for each space. The connectivity between spaces is included by adding the previously detected doors to the reconstructed model. The methodology is tested in a real case study.

a Point Cloud Classification Approach Based on Vertical Structures of Ground Objects

NASA Astrophysics Data System (ADS)

Zhao, Y.; Hu, Q.; Hu, W.

2018-04-01

This paper proposes a novel method for point cloud classification using vertical structural characteristics of ground objects. Since urbanization develops rapidly nowadays, urban ground objects also change frequently. Conventional photogrammetric methods cannot satisfy the requirements of updating the ground objects' information efficiently, so LiDAR (Light Detection and Ranging) technology is employed to accomplish this task. LiDAR data, namely point cloud data, can obtain detailed three-dimensional coordinates of ground objects, but this kind of data is discrete and unorganized. To accomplish ground objects classification with point cloud, we first construct horizontal grids and vertical layers to organize point cloud data, and then calculate vertical characteristics, including density and measures of dispersion, and form characteristic curves for each grids. With the help of PCA processing and K-means algorithm, we analyze the similarities and differences of characteristic curves. Curves that have similar features will be classified into the same class and point cloud correspond to these curves will be classified as well. The whole process is simple but effective, and this approach does not need assistance of other data sources. In this study, point cloud data are classified into three classes, which are vegetation, buildings, and roads. When horizontal grid spacing and vertical layer spacing are 3 m and 1 m respectively, vertical characteristic is set as density, and the number of dimensions after PCA processing is 11, the overall precision of classification result is about 86.31 %. The result can help us quickly understand the distribution of various ground objects.

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 curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

NASA Astrophysics Data System (ADS)

Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

2018-04-01

In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

Evaluation of Methods for Coregistration and Fusion of Rpas-Based 3d Point Clouds and Thermal Infrared Images

NASA Astrophysics Data System (ADS)

Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.

2016-06-01

This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

Aerosol-cloud feedbacks in a turbulent environment: Laboratory measurements representative of conditions in boundary layer clouds

NASA Astrophysics Data System (ADS)

Cantrell, W. H.; Chandrakar, K. K.; Karki, S.; Kinney, G.; Shaw, R.

2017-12-01

Many of the climate impacts of boundary layer clouds are modulated by aerosol particles. As two examples, their interactions with incoming solar and upwelling terrestrial radiation and their propensity for precipitation are both governed by the population of aerosol particles upon which the cloud droplets formed. In turn, clouds are the primary removal mechanism for aerosol particles smaller than a few micrometers and larger than a few nanometers. Aspects of these interconnected phenomena are known in exquisite detail (e.g. Köhler theory), but other parts have not been as amenable to study in the laboratory (e.g. scavenging of aerosol particles by cloud droplets). As a complicating factor, boundary layer clouds are ubiquitously turbulent, which introduces fluctuations in the water vapor concentration and temperature, which govern the saturation ratio which mediates aerosol-cloud interactions. We have performed laboratory measurements of aerosol-cloud coupling and feedbacks, using Michigan Tech's Pi Chamber (Chang et al., 2016). In conditions representative of boundary layer clouds, our data suggest that the lifetime of most interstitial particles in the accumulation mode is governed by cloud activation - particles are removed from the Pi Chamber when they activate and settle out of the chamber as cloud droplets. As cloud droplets are removed, these interstitial particles activate until the initially polluted cloud cleans itself and all particulates are removed from the chamber. At that point, the cloud collapses. Our data also indicate that smaller particles, Dp < ˜ 20 nm are not activated, but are instead removed through diffusion, enhanced by the fact that droplets are moving relative to the suspended aerosol. I will discuss results from both warm (i.e. liquid water only) and mixed phase clouds, showing that cloud and aerosol properties are coupled through fluctuations in the supersaturation, and that threshold behaviors can be defined through the use of the Dämkohler number, the ratio of the characteristic turbulence timescale to the cloud's microphysical response time. Chang, K., et al., 2016. A laboratory facility to study gas-aerosol-cloud interactions in a turbulent environment: The Π Chamber. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-15-00203.1

Analysis of warm convective rain events in Catalonia

NASA Astrophysics Data System (ADS)

Ballart, D.; Figuerola, F.; Aran, M.; Rigo, T.

2009-09-01

Between the end of September and November, events with high amounts of rainfall are quite common in Catalonia. The high sea surface temperature of the Mediterranean Sea near to the Catalan Coast is one of the most important factors that help to the development of this type of storms. Some of these events have particular characteristics: elevated rain rate during short time periods, not very deep convection and low lightning activity. Consequently, the use of remote sensing tools for the surveillance is quite useless or limited. With reference to the high rain efficiency, this is caused by internal mechanisms of the clouds, and also by the air mass where the precipitation structure is developed. As aforementioned, the contribution of the sea to the air mass is very relevant, not only by the increase of the big condensation nuclei, but also by high temperature of the low layers of the atmosphere, where are allowed clouds with 5 or 6 km of particles in liquid phase. In fact, the freezing level into these clouds can be detected by -15ºC. Due to these characteristics, this type of rainy structures can produce high quantities of rainfall in a relatively brief period of time, and, in the case to be quasi-stationary, precipitation values at surface could be very important. From the point of view of remote sensing tools, the cloud nature implies that the different tools and methodologies commonly used for the analysis of heavy rain events are not useful. This is caused by the following features: lightning are rarely observed, the top temperatures of clouds are not cold enough to be enhanced in the satellite imagery, and, finally, reflectivity radar values are lower than other heavy rain cases. The third point to take into account is the vulnerability of the affected areas. An elevated percentage of the Catalan population lives in the coastal region. In the central coast of Catalonia, the urban areas are surrounded by a not very high mountain range with small basins and steep slopes. These factors increase the number of flash floods and the risk indexes. In the present study it is showed the general characteristics of the warm rain events observed in Catalonia, using meteorological, pluviometric, thermodynamic, and remote sensing data. Beside this, other heavy rain events with different features have been analyzed with the purpose of identify the main differences and to improve the knowledge in order to provide enough information for surveillance tasks

Geospatial Field Methods: An Undergraduate Course Built Around Point Cloud Construction and Analysis to Promote Spatial Learning and Use of Emerging Technology in Geoscience

NASA Astrophysics Data System (ADS)

Bunds, M. P.

2017-12-01

Point clouds are a powerful data source in the geosciences, and the emergence of structure-from-motion (SfM) photogrammetric techniques has allowed them to be generated quickly and inexpensively. Consequently, applications of them as well as methods to generate, manipulate, and analyze them warrant inclusion in undergraduate curriculum. In a new course called Geospatial Field Methods at Utah Valley University, students in small groups use SfM to generate a point cloud from imagery collected with a small unmanned aerial system (sUAS) and use it as a primary data source for a research project. Before creating their point clouds, students develop needed technical skills in laboratory and class activities. The students then apply the skills to construct the point clouds, and the research projects and point cloud construction serve as a central theme for the class. Intended student outcomes for the class include: technical skills related to acquiring, processing, and analyzing geospatial data; improved ability to carry out a research project; and increased knowledge related to their specific project. To construct the point clouds, students first plan their field work by outlining the field site, identifying locations for ground control points (GCPs), and loading them onto a handheld GPS for use in the field. They also estimate sUAS flight elevation, speed, and the flight path grid spacing required to produce a point cloud with the resolution required for their project goals. In the field, the students place the GCPs using handheld GPS, and survey the GCP locations using post-processed-kinematic (PPK) or real-time-kinematic (RTK) methods. The students pilot the sUAS and operate its camera according to the parameters that they estimated in planning their field work. Data processing includes obtaining accurate locations for the PPK/RTK base station and GCPs, and SfM processing with Agisoft Photoscan. The resulting point clouds are rasterized into digital surface models, assessed for accuracy, and analyzed in Geographic Information System software. Student projects have included mapping and analyzing landslide morphology, fault scarps, and earthquake ground surface rupture. Students have praised the geospatial skills they learn, whereas helping them stay on schedule to finish their projects is a challenge.

Building a LiDAR point cloud simulator: Testing algorithms for high resolution topographic change

NASA Astrophysics Data System (ADS)

Carrea, Dario; Abellán, Antonio; Derron, Marc-Henri; Jaboyedoff, Michel

2014-05-01

Terrestrial laser technique (TLS) is becoming a common tool in Geosciences, with clear applications ranging from the generation of a high resolution 3D models to the monitoring of unstable slopes and the quantification of morphological changes. Nevertheless, like every measurement techniques, TLS still has some limitations that are not clearly understood and affect the accuracy of the dataset (point cloud). A challenge in LiDAR research is to understand the influence of instrumental parameters on measurement errors during LiDAR acquisition. Indeed, different critical parameters interact with the scans quality at different ranges: the existence of shadow areas, the spatial resolution (point density), and the diameter of the laser beam, the incidence angle and the single point accuracy. The objective of this study is to test the main limitations of different algorithms usually applied on point cloud data treatment, from alignment to monitoring. To this end, we built in MATLAB(c) environment a LiDAR point cloud simulator able to recreate the multiple sources of errors related to instrumental settings that we normally observe in real datasets. In a first step we characterized the error from single laser pulse by modelling the influence of range and incidence angle on single point data accuracy. In a second step, we simulated the scanning part of the system in order to analyze the shifting and angular error effects. Other parameters have been added to the point cloud simulator, such as point spacing, acquisition window, etc., in order to create point clouds of simple and/or complex geometries. We tested the influence of point density and vitiating point of view on the Iterative Closest Point (ICP) alignment and also in some deformation tracking algorithm with same point cloud geometry, in order to determine alignment and deformation detection threshold. We also generated a series of high resolution point clouds in order to model small changes on different environments (erosion, landslide monitoring, etc) and we then tested the use of filtering techniques using 3D moving windows along the space and time, which considerably reduces data scattering due to the benefits of data redundancy. In conclusion, the simulator allowed us to improve our different algorithms and to understand how instrumental error affects final results. And also, improve the methodology of scans acquisition to find the best compromise between point density, positioning and acquisition time with the best accuracy possible to characterize the topographic change.

Measurement of optical blurring in a turbulent cloud chamber

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Ciochetto, David S.; Cantrell, Will H.; Roggemann, Michael C.; Shaw, Raymond A.

2016-10-01

Earth's atmosphere can significantly impact the propagation of electromagnetic radiation, degrading the performance of imaging systems. Deleterious effects of the atmosphere include turbulence, absorption and scattering by particulates. Turbulence leads to blurring, while absorption attenuates the energy that reaches imaging sensors. The optical properties of aerosols and clouds also impact radiation propagation via scattering, resulting in decorrelation from unscattered light. Models have been proposed for calculating a point spread function (PSF) for aerosol scattering, providing a method for simulating the contrast and spatial detail expected when imaging through atmospheres with significant aerosol optical depth. However, these synthetic images and their predicating theory would benefit from comparison with measurements in a controlled environment. Recently, Michigan Technological University (MTU) has designed a novel laboratory cloud chamber. This multiphase, turbulent "Pi Chamber" is capable of pressures down to 100 hPa and temperatures from -55 to +55°C. Additionally, humidity and aerosol concentrations are controllable. These boundary conditions can be combined to form and sustain clouds in an instrumented laboratory setting for measuring the impact of clouds on radiation propagation. This paper describes an experiment to generate mixing and expansion clouds in supersaturated conditions with salt aerosols, and an example of measured imagery viewed through the generated cloud is shown. Aerosol and cloud droplet distributions measured during the experiment are used to predict scattering PSF and MTF curves, and a methodology for validating existing theory is detailed. Measured atmospheric inputs will be used to simulate aerosol-induced image degradation for comparison with measured imagery taken through actual cloud conditions. The aerosol MTF will be experimentally calculated and compared to theoretical expressions. The key result of this study is the proposal of a closure experiment for verification of theoretical aerosol effects using actual clouds in a controlled laboratory setting.

A conceptual weather-type classification procedure for the Philadelphia, Pennsylvania, area

USGS Publications Warehouse

McCabe, Gregory J.

1990-01-01

A simple method of weather-type classification, based on a conceptual model of pressure systems that pass through the Philadelphia, Pennsylvania, area, has been developed. The only inputs required for the procedure are daily mean wind direction and cloud cover, which are used to index the relative position of pressure systems and fronts to Philadelphia.Daily mean wind-direction and cloud-cover data recorded at Philadelphia, Pennsylvania, from January 1954 through August 1988 were used to categorize daily weather conditions. The conceptual weather types reflect changes in daily air and dew-point temperatures, and changes in monthly mean temperature and monthly and annual precipitation. The weather-type classification produced by using the conceptual model was similar to a classification produced by using a multivariate statistical classification procedure. Even though the conceptual weather types are derived from a small amount of data, they appear to account for the variability of daily weather patterns sufficiently to describe distinct weather conditions for use in environmental analyses of weather-sensitive processes.

Magnetic clouds, helicity conservation, and intrinsic scale flux ropes

NASA Technical Reports Server (NTRS)

Kumar, A.; Rust, D. M.

1995-01-01

An intrinsic-scale flux-rope model for interplanetary magnetic clouds, incorporating conservation of magnetic helicity, flux and mass is found to adequately explain clouds' average thermodynamic and magnetic properties. In spite their continuous expansion as they balloon into interplanetary space, magnetic clouds maintain high temperatures. This is shown to be due to magnetic energy dissipation. The temperature of an expanding cloud is shown to pass through a maximum above its starting temperature if the initial plasma beta in the cloud is less than 2/3. Excess magnetic pressure inside the cloud is not an important driver of the expansion as it is almost balanced by the tension in the helical field lines. It is conservation of magnetic helicity and flux that requires that clouds expand radially as they move away from the Sun. Comparison with published data shows good agreement between measured cloud properties and theory. Parameters determined from theoretical fits to the data, when extended back to the Sun, are consistent with the origin of interplanetary magnetic clouds in solar filament eruptions. A possible extension of the heating mechanism discussed here to heating of the solar corona is discussed.

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.

Pressure-temperature gelatinization phase diagram of starch: An in situ Fourier transform infrared study.

PubMed

Rubens, P; Heremans, K

2000-12-01

The gelatinization of rice starch is reported as a function of temperature and pressure from the changes in the ir spectrum. The diagram that is observed is reminiscent of those obtained for the denaturation of proteins and the phase separation observed from the cloud point for several water soluble synthetic polymers. It is proposed that the reentrant shape of the diagram for starch is not only due to hydrogen bonding but also to the imperfect packing of amylose and amylopectin chains in the starch granule. The influence of pressure and temperature on thermodynamic parameters leading to this diagram is discussed. Copyright 2000 John Wiley & Sons, Inc.

Tropical Depression 6 Florence in the Atlantic

NASA Image and Video Library

2006-09-03

This infrared image shows Tropical Depression 6 Florence in the Atlantic, from the Atmospheric Infrared Sounder AIRS on NASA Aqua satellite in September, 2006. Because infrared radiation does not penetrate through clouds, AIRS infrared images show either the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. In cloud-free areas the AIRS instrument will receive the infrared radiation from the surface of the Earth, resulting in the warmest temperatures (orange/red). http://photojournal.jpl.nasa.gov/catalog/PIA00512

NASA Experiment on Tropospheric-Stratospheric Water Vapor Transport in the Intertropical Convergence Zone

NASA Technical Reports Server (NTRS)

Page, William A.

1982-01-01

The following six papers report preliminary results obtained from a field experiment designed to study the role of tropical cumulo-nimbus clouds in the transfer of water vapor from the troposphere to the stratosphere over the region of Panama. The measurements were made utilizing special NOAA enhanced IR satellite images, radiosonde-ozonesondes and a NASA U-2 aircraft carrying. nine experiments. The experiments were provided by a group of NASA, NOAA, industry, and university scientists. Measurements included atmospheric humidity, air and cloud top temperatures, atmospheric tracer constituents, cloud particle characteristics and cloud morphology. The aircraft made a total of eleven flights from August 30 through September 18, 1980, from Howard Air Force Base, Panama; the pilots obtained horizontal and vertical profiles in and near convectively active regions and flew around and over cumulo-nimbus towers and through the extended anvils in the stratosphere. Cumulo-nimbus clouds in the tropics appear to play an important role in upward water vapor transport and may represent the principal source influencing the stratospheric water vapor budget. The clouds provide strong vertical circulation in the troposphere, mixing surface air and its trace materials (water vapor, CFM's sulfur compounds, etc.) quickly up to the tropopause. It is usually assumed that large scale mean motions or eddy scale motions transport the trace materials through the tropopause and into the stratosphere where they are further dispersed and react with other stratospheric constituents. The important step between the troposphere and stratosphere for water vapor appears to depend upon the processes occurring at or near the tropopause at the tops of the cumulo-nimbus towers. Several processes have been sugested: (1) The highest towers penetrate the tropopause and carry water in the form of small ice particles directly into the stratosphere. (2) Water vapor from the tops of the cumulonimbus clouds is transported somehow through the tropopause, the vapor pressure being controlled by the temperature at the tops of the clouds; the dryness of the stratosphere could be explained if most of the transport occurs in connection with very high clouds in regions with very high and cold tropopause. (3) Cumulo-nimbus anvils act as terrestrial-radiation shields allowing the ice particle temperatures near cloud tops to cool radiatively below the supersaturation point; this cooling would cause a vapor deposition on the ice particles which will settle out and thus act as water scavengers. The experiment was designed to collect information on these detailed physical processes near and above the tropopause in order to assess their importance and the role they play in controlling stratospheric water vapor humidity.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations.

PubMed

Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao

2017-04-11

A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10-0.20 m, and vertical accuracy was approximately 0.01-0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed.

The temperature of large dust grains in molecular clouds

NASA Technical Reports Server (NTRS)

Clark, F. O.; Laureijs, R. J.; Prusti, T.

1991-01-01

The temperature of the large dust grains is calculated from three molecular clouds ranging in visual extinction from 2.5 to 8 mag, by comparing maps of either extinction derived from star counts or gas column density derived from molecular observations to I(100). Both techniques show the dust temperature declining into clouds. The two techniques do not agree in absolute scale.

Advanced Visualization and Interactive Display Rapid Innovation and Discovery Evaluation Research (VISRIDER) Program Task 6: Point Cloud Visualization Techniques for Desktop and Web Platforms

DTIC Science & Technology

2017-04-01

ADVANCED VISUALIZATION AND INTERACTIVE DISPLAY RAPID INNOVATION AND DISCOVERY EVALUATION RESEARCH (VISRIDER) PROGRAM TASK 6: POINT CLOUD...To) OCT 2013 – SEP 2014 4. TITLE AND SUBTITLE ADVANCED VISUALIZATION AND INTERACTIVE DISPLAY RAPID INNOVATION AND DISCOVERY EVALUATION RESEARCH...various point cloud visualization techniques for viewing large scale LiDAR datasets. Evaluate their potential use for thick client desktop platforms

Inventory of File WAFS_blended_2014102006f06.grib2

Science.gov Websites

) [%] 004 700 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial ave,code table 4.15=3,#points=1 005 700 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial max,code table 4.15=3,#points=1 006 600 mb CTP 6 hour fcst In-Cloud Turbulence [%] spatial ave,code table 4.15=3,#points=1 007 600 mb CTP 6 hour fcst In

Airborne lidar/radiometric measurements of cirrus cloud parameters and their application to LOWTRAN radiance evaluations

NASA Technical Reports Server (NTRS)

Uthe, Edward E.

1990-01-01

SRI has assembled an airborne lidar/radiometric instrumentation suite for mapping cirrus cloud distribution and analyzing cirrus cloud optical properties. Operation of upward viewing infrared radiometers from an airborne platform provides the optimum method of measuring high altitude cold cloud radiative properties with minimum interference from the thermal emission by the earth's surface and lower atmospheric components. Airborne installed sensors can also operate over large regional areas including water, urban, and mountain surfaces and above lower atmospheric convective clouds and haze layers. Currently available sensors installed on the SRI Queen Air aircraft are illustrated. Lidar and radiometric data records are processed for real time viewing on a color video screen. A cirrus cloud data example is presented as a black and white reproduction of a color display of data at the aircraft altitude of 12,000 ft, the 8 to 14 micron atmospheric radiation background was equivalent to a blackbody temperature of about -60 C and, therefore, the radiometer did not respond strongly to low density cirrus cloud concentrations detected by the lidar. Cloud blackbody temperatures (observed by radiometer) are shown plotted against midcloud temperatures (derived from lidar observed cloud heights and supporting temperature profiles) for data collected on 30 June and 28 July.

Continuous Lidar Monitoring of Polar Stratospheric Clouds at the South Pole

NASA Technical Reports Server (NTRS)

Campbell, James R.; Welton, Ellsworth J.; Spinhirne, James D

2009-01-01

Polar stratospheric clouds (PSC) play a primary role in the formation of annual ozone holes over Antarctica during the austral sunrise. Meridional temperature gradients in the lower stratosphere and upper troposphere, caused by strong radiative cooling, induce a broad dynamic vortex centered near the South Pole that decouples and insulates the winter polar airmass. PSC nucleate and grow as vortex temperatures gradually fall below equilibrium saturation and frost points for ambient sulfate, nitrate, and water vapor concentrations (generally below 197 K). Cloud surfaces promote heterogeneous reactions that convert stable chlorine and bromine-based molecules into photochemically active ones. As spring nears, and the sun reappears and rises, photolysis decomposes these partitioned compounds into individual halogen atoms that react with and catalytically destroy thousands of ozone molecules before they are stochastically neutralized. Despite a generic understanding of the ozone hole paradigm, many key components of the system, such as cloud occurrence, phase, and composition; particle growth mechanisms; and denitrification of the lower stratosphere have yet to be fully resolved. Satellite-based observations have dramatically improved the ability to detect PSC and quantify seasonal polar chemical partitioning. However, coverage directly over the Antarctic plateau is limited by polar-orbiting tracks that rarely exceed 80 degrees S. In December 1999, a NASA Micropulse Lidar Network instrument (MPLNET) was first deployed to the NOAA Earth Systems Research Laboratory (ESRL) Atmospheric Research Observatory at the Amundsen-Scott South Pole Station for continuous cloud and aerosol profiling. MPLNET instruments are eye-safe, capable of full-time autonomous operation, and suitably rugged and compact to withstand long-term remote deployment. With only brief interruptions during the winters of 2001 and 2002, a nearly continuous data archive exists to the present.

3D Surface Temperature Measurement of Plant Canopies Using Photogrammetry Techniques From A UAV.

NASA Astrophysics Data System (ADS)

Irvine, M.; Lagouarde, J. P.

2017-12-01

Surface temperature of plant canopies and within canopies results from the coupling of radiative and energy exchanges processes which govern the fluxes at the interface soil-plant-atmosphere. As a key parameter, surface temperature permits the estimation of canopy exchanges using processes based modeling methods. However detailed 3D surface temperature measurements or even profile surface temperature measurements are rarely made as they have inherent difficulties. Such measurements would greatly improve multi-level canopy models such as NOAH (Chen and Dudhia 2001) or MuSICA (Ogée and Brunet 2002, Ogée et al 2003) where key surface temperature estimations, at present, are not tested. Additionally, at larger scales, canopy structure greatly influences satellite based surface temperature measurements as the structure impacts the observations which are intrinsically made at varying satellite viewing angles and solar heights. In order to account for these differences, again accurate modeling is required such as through the above mentioned multi-layer models or with several source type models such as SCOPE (Van der Tol 2009) in order to standardize observations. As before, in order to validate these models, detailed field observations are required. With the need for detailed surface temperature observations in mind we have planned a series of experiments over non-dense plant canopies to investigate the use of photogrammetry techniques. Photogrammetry is normally used for visible wavelengths to produce 3D images using cloud point reconstruction of aerial images (for example Dandois and Ellis, 2010, 2013 over a forest). From these cloud point models it should be possible to establish 3D plant surface temperature images when using thermal infrared array sensors. In order to do this our experiments are based on the use of a thermal Infrared camera embarked on a UAV. We adapt standard photogrammetry to account for limits imposed by thermal imaginary, especially the low image resolution compared with standard RGB sensors. At the session B081, we intend to present first results of our thermal photogrammetric experiments with 3D surface temperature plots in order to discuss and adapt our methods to the modelling community's needs.

Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

PubMed Central

Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

2014-01-01

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated. PMID:24737962

Observations of the boundary layer, cloud, and aerosol variability in the southeast Pacific near-coastal marine stratocumulus during VOCALS-REx

NASA Astrophysics Data System (ADS)

Zheng, X.; Albrecht, B.; Jonsson, H. H.; Khelif, D.; Feingold, G.; Minnis, P.; Ayers, K.; Chuang, P.; Donaher, S.; Rossiter, D.; Ghate, V.; Ruiz-Plancarte, J.; Sun-Mack, S.

2011-09-01

Aircraft observations made off the coast of northern Chile in the Southeastern Pacific (20° S, 72° W; named Point Alpha) from 16 October to 13 November 2008 during the VAMOS Ocean-Cloud- Atmosphere-Land Study-Regional Experiment (VOCALS-REx), combined with meteorological reanalysis, satellite measurements, and radiosonde data, are used to investigate the boundary layer (BL) and aerosol-cloud-drizzle variations in this region. On days without predominately synoptic and meso-scale influences, the BL at Point Alpha was typical of a non-drizzling stratocumulus-topped BL. Entrainment rates calculated from the near cloud-top fluxes and turbulence in the BL at Point Alpha appeared to be weaker than those in the BL over the open ocean west of Point Alpha and the BL near the coast of the northeast Pacific. The cloud liquid water path (LWP) varied between 15 g m-2 and 160 g m-2. The BL had a depth of 1140 ± 120 m, was generally well-mixed and capped by a sharp inversion without predominately synoptic and meso-scale influences. The wind direction generally switched from southerly within the BL to northerly above the inversion. On days when a synoptic system and related mesoscale costal circulations affected conditions at Point Alpha (29 October-4 November), a moist layer above the inversion moved over Point Alpha, and the total-water mixing ratio above the inversion was larger than that within the BL. The accumulation mode aerosol varied from 250 to 700 cm-3 within the BL, and CCN at 0.2 % supersaturation within the BL ranged between 150 and 550 cm-3. The main aerosol source at Point Alpha was horizontal advection within the BL from south. The average cloud droplet number concentration ranged between 80 and 400 cm-3. While the mean LWP retrieved from GOES was in good agreement with the in situ measurements, the GOES-derived cloud droplet effective radius tended to be larger than that from the aircraft in situ observations near cloud top. The aerosol and cloud LWP relationship reveals that during the typical well-mixed BL days the cloud LWP increased with the CCN concentrations. On the other hand, meteorological factors and the decoupling processes have large influences on the cloud LWP variation as well.

Impact of survey workflow on precision and accuracy of terrestrial LiDAR datasets

NASA Astrophysics Data System (ADS)

Gold, P. O.; Cowgill, E.; Kreylos, O.

2009-12-01

Ground-based LiDAR (Light Detection and Ranging) survey techniques are enabling remote visualization and quantitative analysis of geologic features at unprecedented levels of detail. For example, digital terrain models computed from LiDAR data have been used to measure displaced landforms along active faults and to quantify fault-surface roughness. But how accurately do terrestrial LiDAR data represent the true ground surface, and in particular, how internally consistent and precise are the mosaiced LiDAR datasets from which surface models are constructed? Addressing this question is essential for designing survey workflows that capture the necessary level of accuracy for a given project while minimizing survey time and equipment, which is essential for effective surveying of remote sites. To address this problem, we seek to define a metric that quantifies how scan registration error changes as a function of survey workflow. Specifically, we are using a Trimble GX3D laser scanner to conduct a series of experimental surveys to quantify how common variables in field workflows impact the precision of scan registration. Primary variables we are testing include 1) use of an independently measured network of control points to locate scanner and target positions, 2) the number of known-point locations used to place the scanner and point clouds in 3-D space, 3) the type of target used to measure distances between the scanner and the known points, and 4) setting up the scanner over a known point as opposed to resectioning of known points. Precision of the registered point cloud is quantified using Trimble Realworks software by automatic calculation of registration errors (errors between locations of the same known points in different scans). Accuracy of the registered cloud (i.e., its ground-truth) will be measured in subsequent experiments. To obtain an independent measure of scan-registration errors and to better visualize the effects of these errors on a registered point cloud, we scan from multiple locations an object of known geometry (a cylinder mounted above a square box). Preliminary results show that even in a controlled experimental scan of an object of known dimensions, there is significant variability in the precision of the registered point cloud. For example, when 3 scans of the central object are registered using 4 known points (maximum time, maximum equipment), the point clouds align to within ~1 cm (normal to the object surface). However, when the same point clouds are registered with only 1 known point (minimum time, minimum equipment), misalignment of the point clouds can range from 2.5 to 5 cm, depending on target type. The greater misalignment of the 3 point clouds when registered with fewer known points stems from the field method employed in acquiring the dataset and demonstrates the impact of field workflow on LiDAR dataset precision. By quantifying the degree of scan mismatch in results such as this, we can provide users with the information needed to maximize efficiency in remote field surveys.

STAR FORMATION IN THE MOLECULAR CLOUD ASSOCIATED WITH THE MONKEY HEAD NEBULA: SEQUENTIAL OR SPONTANEOUS?

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

Chibueze, James O.; Imura, Kenji; Omodaka, Toshihiro

2013-01-01

We mapped the (1,1), (2,2), and (3,3) lines of NH{sub 3} toward the molecular cloud associated with the Monkey Head Nebula (MHN) with a 1.'6 angular resolution using a Kashima 34 m telescope operated by the National Institute of Information and Communications Technology (NICT). The kinetic temperature of the molecular gas is 15-30 K in the eastern part and 30-50 K in the western part. The warmer gas is confined to a small region close to the compact H II region S252A. The cooler gas is extended over the cloud even near the extended H II region, the MHN. Wemore » made radio continuum observations at 8.4 GHz using the Yamaguchi 32 m radio telescope. The resultant map shows no significant extension from the H{alpha} image. This means that the molecular cloud is less affected by the MHN, suggesting that the molecular cloud did not form by the expanding shock of the MHN. Although the spatial distribution of the Wide-field Infrared Survey Explorer and Two Micron All Sky Survey point sources suggests that triggered low- and intermediate-mass star formation took place locally around S252A, but the exciting star associated with it should be formed spontaneously in the molecular cloud.« less

The origin of recombining plasma and the detection of the Fe-K line in the supernova remnant W 28

NASA Astrophysics Data System (ADS)

Okon, Hiromichi; Uchida, Hiroyuki; Tanaka, Takaaki; Matsumura, Hideaki; Tsuru, Takeshi Go

2018-03-01

Overionized recombining plasmas (RPs) have been discovered from a dozen mixed-morphology (MM) supernova remnants (SNRs). However, their formation process is still under debate. As pointed out by many previous studies, spatial variations of plasma temperature and ionization state provide clues to understanding the physical origin of RPs. We report on spatially resolved X-ray spectroscopy of W 28, which is one of the largest MM SNRs found in our Galaxy. Two observations with Suzaku XIS cover the center of W 28 to the northeastern rim where the shock is interacting with molecular clouds. The X-ray spectra in the inner regions are reproduced well by a combination of two RP models with different temperatures and ionization states, whereas that in the northeastern rim is explained with a single RP model. Our discovery of the RP in the northeastern rim suggests an effect of thermal conduction between the cloud and hot plasma, which may be the production process of the RP. The X-ray spectrum of the northeastern rim also shows an excess emission of the Fe I K α line. The most probable process to explain the line would be inner shell ionization of Fe in the molecular cloud by cosmic ray particles accelerated in W 28.

The origin of recombining plasma and the detection of the Fe-K line in the supernova remnant W 28

NASA Astrophysics Data System (ADS)

Okon, Hiromichi; Uchida, Hiroyuki; Tanaka, Takaaki; Matsumura, Hideaki; Tsuru, Takeshi Go

2018-06-01

Overionized recombining plasmas (RPs) have been discovered from a dozen mixed-morphology (MM) supernova remnants (SNRs). However, their formation process is still under debate. As pointed out by many previous studies, spatial variations of plasma temperature and ionization state provide clues to understanding the physical origin of RPs. We report on spatially resolved X-ray spectroscopy of W 28, which is one of the largest MM SNRs found in our Galaxy. Two observations with Suzaku XIS cover the center of W 28 to the northeastern rim where the shock is interacting with molecular clouds. The X-ray spectra in the inner regions are reproduced well by a combination of two RP models with different temperatures and ionization states, whereas that in the northeastern rim is explained with a single RP model. Our discovery of the RP in the northeastern rim suggests an effect of thermal conduction between the cloud and hot plasma, which may be the production process of the RP. The X-ray spectrum of the northeastern rim also shows an excess emission of the Fe I K α line. The most probable process to explain the line would be inner shell ionization of Fe in the molecular cloud by cosmic ray particles accelerated in W 28.

A 3D clustering approach for point clouds to detect and quantify changes at a rock glacier front

NASA Astrophysics Data System (ADS)

Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

2016-04-01

Terrestrial Laser Scanners (TLS) are extensively used in geomorphology to remotely-sense landforms and surfaces of any type and to derive digital elevation models (DEMs). Modern devices are able to collect many millions of points, so that working on the resulting dataset is often troublesome in terms of computational efforts. Indeed, it is not unusual that raw point clouds are filtered prior to DEM creation, so that only a subset of points is retained and the interpolation process becomes less of a burden. Whilst this procedure is in many cases necessary, it implicates a considerable loss of valuable information. First, and even without eliminating points, the common interpolation of points to a regular grid causes a loss of potentially useful detail. Second, it inevitably causes the transition from 3D information to only 2.5D data where each (x,y) pair must have a unique z-value. Vector-based DEMs (e.g. triangulated irregular networks) partially mitigate these issues, but still require a set of parameters to be set and a considerable burden in terms of calculation and storage. Because of the reasons above, being able to perform geomorphological research directly on point clouds would be profitable. Here, we propose an approach to identify erosion and deposition patterns on a very active rock glacier front in the Swiss Alps to monitor sediment dynamics. The general aim is to set up a semiautomatic method to isolate mass movements using 3D-feature identification directly from LiDAR data. An ultra-long range LiDAR RIEGL VZ-6000 scanner was employed to acquire point clouds during three consecutive summers. In order to isolate single clusters of erosion and deposition we applied the Density-Based Scan Algorithm with Noise (DBSCAN), previously successfully employed by Tonini and Abellan (2014) in a similar case for rockfall detection. DBSCAN requires two input parameters, strongly influencing the number, shape and size of the detected clusters: the minimum number of points (i) at a maximum distance (ii) around each core-point. Under this condition, seed points are said to be density-reachable by a core point delimiting a cluster around it. A chain of intermediate seed-points can connect contiguous clusters allowing clusters of arbitrary shape to be defined. The novelty of the proposed approach consists in the implementation of the DBSCAN 3D-module, where the xyz-coordinates identify each point and the density of points within a sphere is considered. This allows detecting volumetric features with a higher accuracy, depending only on actual sampling resolution. The approach is truly 3D and exploits all TLS measurements without the need of interpolation or data reduction. Using this method, enhanced geomorphological activity during the summer of 2015 in respect to the previous two years was observed. We attribute this result to the exceptionally high temperatures of that summer, which we deem responsible for accelerating the melting process at the rock glacier front and probably also increasing creep velocities. References: - Tonini, M. and Abellan, A. (2014). Rockfall detection from terrestrial LiDAR point clouds: A clustering approach using R. Journal of Spatial Information Sciences. Number 8, pp95-110 - Hennig, C. Package fpc: Flexible procedures for clustering. https://cran.r-project.org/web/packages/fpc/index.html, 2015. Accessed 2016-01-12.

Stereographic observations from geosynchronous satellites - An important new tool for the atmospheric sciences

NASA Technical Reports Server (NTRS)

Hasler, A. F.

1981-01-01

Observations of cloud geometry using scan-synchronized stereo geostationary satellites having images with horizontal spatial resolution of approximately 0.5 km, and temporal resolution of up to 3 min are presented. The stereo does not require a cloud with known emissivity to be in equilibrium with an atmosphere with a known vertical temperature profile. It is shown that absolute accuracies of about 0.5 km are possible. Qualitative and quantitative representations of atmospheric dynamics were shown by remapping, display, and stereo image analysis on an interactive computer/imaging system. Applications of stereo observations include: (1) cloud top height contours of severe thunderstorms and hurricanes, (2) cloud top and base height estimates for cloud-wind height assignment, (3) cloud growth measurements for severe thunderstorm over-shooting towers, (4) atmospheric temperature from stereo heights and infrared cloud top temperatures, and (5) cloud emissivity estimation. Recommendations are given for future improvements in stereo observations, including a third GOES satellite, operational scan synchronization of all GOES satellites and better resolution sensors.

Comparison of 3D point clouds produced by LIDAR and UAV photoscan in the Rochefort cave (Belgium)

NASA Astrophysics Data System (ADS)

Watlet, Arnaud; Triantafyllou, Antoine; Kaufmann, Olivier; Le Mouelic, Stéphane

2016-04-01

Amongst today's techniques that are able to produce 3D point clouds, LIDAR and UAV (Unmanned Aerial Vehicle) photogrammetry are probably the most commonly used. Both methods have their own advantages and limitations. LIDAR scans create high resolution and high precision 3D point clouds, but such methods are generally costly, especially for sporadic surveys. Compared to LIDAR, UAV (e.g. drones) are cheap and flexible to use in different kind of environments. Moreover, the photogrammetric processing workflow of digital images taken with UAV becomes easier with the rise of many affordable software packages (e.g. Agisoft, PhotoModeler3D, VisualSFM). We present here a challenging study made at the Rochefort Cave Laboratory (South Belgium) comprising surface and underground surveys. The site is located in the Belgian Variscan fold-and-thrust belt, a region that shows many karstic networks within Devonian limestone units. A LIDAR scan has been acquired in the main chamber of the cave (~ 15000 m³) to spatialize 3D point cloud of its inner walls and infer geological beds and structures. Even if the use of LIDAR instrument was not really comfortable in such caving environment, the collected data showed a remarkable precision according to few control points geometry. We also decided to perform another challenging survey of the same cave chamber by modelling a 3D point cloud using photogrammetry of a set of DSLR camera pictures taken from the ground and UAV pictures. The aim was to compare both techniques in terms of (i) implementation of data acquisition and processing, (ii) quality of resulting 3D points clouds (points density, field vs cloud recovery and points precision), (iii) their application for geological purposes. Through Rochefort case study, main conclusions are that LIDAR technique provides higher density point clouds with slightly higher precision than photogrammetry method. However, 3D data modeled by photogrammetry provide visible light spectral information for each modeled voxel and interpolated vertices that can be a useful attributes for clustering during data treatment. We thus illustrate such applications to the Rochefort cave by using both sources of 3D information to quantify the orientation of inaccessible geological structures (e.g. faults, tectonic and gravitational joints, and sediments bedding), cluster these structures using color information gathered from UAV's 3D point cloud and compare these data to structural data surveyed on the field. An additional drone photoscan was also conducted in the surface sinkhole giving access to the surveyed underground cavity to seek geological bodies' connections.

On the relationships among cloud cover, mixed-phase partitioning, and planetary albedo in GCMs

DOE PAGES

McCoy, Daniel T.; Tan, Ivy; Hartmann, Dennis L.; ...

2016-05-06

In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean-state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed-phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed-phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water wouldmore » also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti-correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti-correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature-dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble.« less

Study into Point Cloud Geometric Rigidity and Accuracy of TLS-Based Identification of Geometric Bodies

NASA Astrophysics Data System (ADS)

Klapa, Przemyslaw; Mitka, Bartosz; Zygmunt, Mariusz

2017-12-01

Capability of obtaining a multimillion point cloud in a very short time has made the Terrestrial Laser Scanning (TLS) a widely used tool in many fields of science and technology. The TLS accuracy matches traditional devices used in land surveying (tacheometry, GNSS - RTK), but like any measurement it is burdened with error which affects the precise identification of objects based on their image in the form of a point cloud. The point’s coordinates are determined indirectly by means of measuring the angles and calculating the time of travel of the electromagnetic wave. Each such component has a measurement error which is translated into the final result. The XYZ coordinates of a measuring point are determined with some uncertainty and the very accuracy of determining these coordinates is reduced as the distance to the instrument increases. The paper presents the results of examination of geometrical stability of a point cloud obtained by means terrestrial laser scanner and accuracy evaluation of solids determined using the cloud. Leica P40 scanner and two different settings of measuring points were used in the tests. The first concept involved placing a few balls in the field and then scanning them from various sides at similar distances. The second part of measurement involved placing balls and scanning them a few times from one side but at varying distances from the instrument to the object. Each measurement encompassed a scan of the object with automatic determination of its position and geometry. The desk studies involved a semiautomatic fitting of solids and measurement of their geometrical elements, and comparison of parameters that determine their geometry and location in space. The differences of measures of geometrical elements of balls and translations vectors of the solids centres indicate the geometrical changes of the point cloud depending on the scanning distance and parameters. The results indicate the changes in the geometry of scanned objects depending on the point cloud quality and distance from the measuring instrument. Varying geometrical dimensions of the same element suggest also that the point cloud does not keep a stable geometry of measured objects.

Temperature uniformity in the CERN CLOUD chamber

NASA Astrophysics Data System (ADS)

Dias, António; Ehrhart, Sebastian; Vogel, Alexander; Williamson, Christina; Almeida, João; Kirkby, Jasper; Mathot, Serge; Mumford, Samuel; Onnela, Antti

2017-12-01

The CLOUD (Cosmics Leaving OUtdoor Droplets) experiment at CERN (European Council for Nuclear Research) investigates the nucleation and growth of aerosol particles under atmospheric conditions and their activation into cloud droplets. A key feature of the CLOUD experiment is precise control of the experimental parameters. Temperature uniformity and stability in the chamber are important since many of the processes under study are sensitive to temperature and also to contaminants that can be released from the stainless steel walls by upward temperature fluctuations. The air enclosed within the 26 m3 CLOUD chamber is equipped with several arrays (strings) of high precision, fast-response thermometers to measure its temperature. Here we present a study of the air temperature uniformity inside the CLOUD chamber under various experimental conditions. Measurements were performed under calibration conditions and run conditions, which are distinguished by the flow rate of fresh air and trace gases entering the chamber at 20 and up to 210 L min-1, respectively. During steady-state calibration runs between -70 and +20 °C, the air temperature uniformity is better than ±0.06 °C in the radial direction and ±0.1 °C in the vertical direction. Larger non-uniformities are present during experimental runs, depending on the temperature control of the make-up air and trace gases (since some trace gases require elevated temperatures until injection into the chamber). The temperature stability is ±0.04 °C over periods of several hours during either calibration or steady-state run conditions. During rapid adiabatic expansions to activate cloud droplets and ice particles, the chamber walls are up to 10 °C warmer than the enclosed air. This results in temperature differences of ±1.5 °C in the vertical direction and ±1 °C in the horizontal direction, while the air returns to its equilibrium temperature with a time constant of about 200 s.

Options to Improve Rain Snow Parameterization in Surface Based Models

NASA Astrophysics Data System (ADS)

Feiccabrino, J. M.

2017-12-01

Precipitation phase determination is of upmost importance in a number of surface based hydrological, ecological, and safety models. However, precipitation phase at Earth's surface is a result of cloud and atmospheric properties not measured by surface weather stations. Nonetheless, they can be inferred from the available surface datum. This study uses 681,620 weather observations with air temperatures between -3 and 5°C and identified precipitation occurring at the time of the observation to determine simple, yet accurate, thresholds for precipitation phase determination schemes (PPDS). This dataset represents 38% and 42% of precipitation observations over a 16 year period for 85 Swedish, and 84 Norwegian weather stations. The misclassified precipitation (error) from PPDS using AT, dew-point temperature (DT) and wet-bulb temperature (WB) thresholds were compared using a single threshold PPDS. The Norwegian observations between -3 and 5°C resulted in 11.64%, 11.21%, and 8.42% error for DT (-0.2°C), AT (1.2°C), and WB (0.3°C) thresholds respectively. Individual station thresholds had a range of -0.7 to 1.2°C, -1.2 to 0.9°C, and -0.1 to 2.5°C for WB, DP, and AT respectively. To address threshold variance while decreasing error, weather stations were grouped into nine landscape categories; windward (WW) ocean, WW coast, WW fjord, WW hill, WW mountain, leeward (LW) mountain, LW hill, LW rolling hills, and LW coast. Landscape classification was based on location relative to the Scandinavian Mountains, and the % water or range of elevation within 15KM. Within landscapes, stations share similar land atmosphere exchanges which differ from other landscapes. These differences change optimal thresholds for PPDS between landscapes. Also tested were threshold temperature affects based on assumed atmospheric differences for the following observation groups; 1.) occurring before and after an air mass boundary, 2.) with different water temperatures and/or NAO phases, 3.) with snow cover, 4.) coupled with higher elevation stations and 5.) with different cloud heights. For example, in Norway, as the unsaturated layer depth beneath clouds increased, AT thresholds warmed. Cloud height adjusted AT thresholds reduced error by 5% before threshold adjustments for landscapes.

Structure-From for Calibration of a Vehicle Camera System with Non-Overlapping Fields-Of in AN Urban Environment

NASA Astrophysics Data System (ADS)

Hanel, A.; Stilla, U.

2017-05-01

Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between one and ten centimeters from tachymeter reference measurements.

Comparison of 3D point clouds obtained by photogrammetric UAVs and TLS to determine the attitude of dolerite outcrops discontinuities.

NASA Astrophysics Data System (ADS)

Duarte, João; Gonçalves, Gil; Duarte, Diogo; Figueiredo, Fernando; Mira, Maria

2015-04-01

Photogrammetric Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) are two emerging technologies that allows the production of dense 3D point clouds of the sensed topographic surfaces. Although image-based stereo-photogrammetric point clouds could not, in general, compete on geometric quality over TLS point clouds, fully automated mapping solutions based on ultra-light UAVs (or drones) have recently become commercially available at very reasonable accuracy and cost for engineering and geological applications. The purpose of this paper is to compare the two point clouds generated by these two technologies, in order to automatize the manual process tasks commonly used to detect and represent the attitude of discontinuities (Stereographic projection: Schmidt net - Equal area). To avoid the difficulties of access and guarantee the data survey security conditions, this fundamental step in all geological/geotechnical studies, applied to the extractive industry and engineering works, has to be replaced by a more expeditious and reliable methodology. This methodology will allow, in a more actuated clear way, give answers to the needs of evaluation of rock masses, by mapping the structures present, which will reduce considerably the associated risks (investment, structures dimensioning, security, etc.). A case study of a dolerite outcrop locate in the center of Portugal (the dolerite outcrop is situated in the volcanic complex of Serra de Todo-o-Mundo, Casais Gaiola, intruded in Jurassic sandstones) will be used to assess this methodology. The results obtained show that the 3D point cloud produced by the Photogrammetric UAV platform has the appropriate geometric quality for extracting the parameters that define the discontinuities of the dolerite outcrops. Although, they are comparable to the manual extracted parameters, their quality is inferior to parameters extracted from the TLS point cloud.

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

NASA Technical Reports Server (NTRS)

Slobin, S. D.

1982-01-01

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

Cloud-point detection using a portable thickness shear mode crystal resonator

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

Mansure, A.J.; Spates, J.J.; Germer, J.W.

1997-08-01

The Thickness Shear Mode (TSM) crystal resonator monitors the crude oil by propagating a shear wave into the oil. The coupling of the shear wave and the crystal vibrations is a function of the viscosity of the oil. By driving the crystal with circuitry that incorporates feedback, it is possible to determine the change from Newtonian to non-Newtonian viscosity at the cloud point. A portable prototype TSM Cloud Point Detector (CPD) has performed flawlessly during field and lab tests proving the technique is less subjective or operator dependent than the ASTM standard. The TSM CPD, in contrast to standard viscositymore » techniques, makes the measurement in a closed container capable of maintaining up to 100 psi. The closed container minimizes losses of low molecular weight volatiles, allowing samples (25 ml) to be retested with the addition of chemicals. By cycling/thermal soaking the sample, the effects of thermal history can be investigated and eliminated as a source of confusion. The CPD is portable, suitable for shipping the field offices for use by personnel without special training or experience in cloud point measurements. As such, it can make cloud point data available without the delays and inconvenience of sending samples to special labs. The crystal resonator technology can be adapted to in-line monitoring of cloud point and deposition detection.« less

Metric Scale Calculation for Visual Mapping Algorithms

NASA Astrophysics Data System (ADS)

Hanel, A.; Mitschke, A.; Boerner, R.; Van Opdenbosch, D.; Hoegner, L.; Brodie, D.; Stilla, U.

2018-05-01

Visual SLAM algorithms allow localizing the camera by mapping its environment by a point cloud based on visual cues. To obtain the camera locations in a metric coordinate system, the metric scale of the point cloud has to be known. This contribution describes a method to calculate the metric scale for a point cloud of an indoor environment, like a parking garage, by fusing multiple individual scale values. The individual scale values are calculated from structures and objects with a-priori known metric extension, which can be identified in the unscaled point cloud. Extensions of building structures, like the driving lane or the room height, are derived from density peaks in the point distribution. The extension of objects, like traffic signs with a known metric size, are derived using projections of their detections in images onto the point cloud. The method is tested with synthetic image sequences of a drive with a front-looking mono camera through a virtual 3D model of a parking garage. It has been shown, that each individual scale value improves either the robustness of the fused scale value or reduces its error. The error of the fused scale is comparable to other recent works.

Femtosecond laser filament induced condensation and precipitation in a cloud chamber

PubMed Central

Ju, Jingjing; Liu, Jiansheng; Liang, Hong; Chen, Yu; Sun, Haiyi; Liu, Yonghong; Wang, Jingwei; Wang, Cheng; Wang, Tiejun; Li, Ruxin; Xu, Zhizhan; Chin, See Leang

2016-01-01

A unified picture of femtosecond laser induced precipitation in a cloud chamber is proposed. Among the three principal consequences of filamentation from the point of view of thermodynamics, namely, generation of chemicals, shock waves and thermal air flow motion (due to convection), the last one turns out to be the principal cause. Much of the filament induced chemicals would stick onto the existing background CCN’s (Cloud Condensation Nuclei) through collision making the latter more active. Strong mixing of air having a large temperature gradient would result in supersaturation in which the background CCN’s would grow efficiently into water/ice/snow. This conclusion was supported by two independent experiments using pure heating or a fan to imitate the laser-induced thermal effect or the strong air flow motion, respectively. Without the assistance of any shock wave and chemical CCN’s arising from laser filament, condensation and precipitation occurred. Meanwhile we believe that latent heat release during condensation /precipitation would enhance the air flow for mixing. PMID:27143227

GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites.

PubMed

Leinweber, Matthias; Fober, Thomas; Freisleben, Bernd

2018-01-01

In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.

Real object-based 360-degree integral-floating display using multiple depth camera

NASA Astrophysics Data System (ADS)

Erdenebat, Munkh-Uchral; Dashdavaa, Erkhembaatar; Kwon, Ki-Chul; Wu, Hui-Ying; Yoo, Kwan-Hee; Kim, Young-Seok; Kim, Nam

2015-03-01

A novel 360-degree integral-floating display based on the real object is proposed. The general procedure of the display system is similar with conventional 360-degree integral-floating displays. Unlike previously presented 360-degree displays, the proposed system displays the 3D image generated from the real object in 360-degree viewing zone. In order to display real object in 360-degree viewing zone, multiple depth camera have been utilized to acquire the depth information around the object. Then, the 3D point cloud representations of the real object are reconstructed according to the acquired depth information. By using a special point cloud registration method, the multiple virtual 3D point cloud representations captured by each depth camera are combined as single synthetic 3D point cloud model, and the elemental image arrays are generated for the newly synthesized 3D point cloud model from the given anamorphic optic system's angular step. The theory has been verified experimentally, and it shows that the proposed 360-degree integral-floating display can be an excellent way to display real object in the 360-degree viewing zone.

The Feasibility of 3d Point Cloud Generation from Smartphones

NASA Astrophysics Data System (ADS)

Alsubaie, N.; El-Sheimy, N.

2016-06-01

This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.

Economic Value of Narrowing the Uncertainty in Climate Sensitivity: Decadal Change in Shortwave Cloud Radiative Forcing and Low Cloud Feedback

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R. M.; Golub, A. A.; Mlynczak, M. G.; Young, D. F.; Baize, R. R.

2016-12-01

Several previous studies have been published on the economic value of narrowing the uncertainty in climate sensitivity (Cooke et al. 2015, Cooke et al. 2016, Hope, 2015). All three of these studies estimated roughly 10 Trillion U.S. dollars for the Net Present Value and Real Option Value at a discount rate of 3%. This discount rate is the nominal discount rate used in the U.S. Social Cost of Carbon Memo (2010). The Cooke et al studies approached this problem by examining advances in accuracy of global temperature measurements, while the Hope 2015 study did not address the type of observations required. While temperature change is related to climate sensitivity, large uncertainties of a factor of 3 in current anthropogenic radiative forcing (IPCC, 2013) would need to be solved for advanced decadal temperature change observations to assist the challenge of narrowing climate sensitivity. The present study takes a new approach by extending the Cooke et al. 2015,2016 papers to replace observations of temperature change to observations of decadal change in the effects of changing clouds on the Earths radiative energy balance, a measurement known as Cloud Radiative Forcing, or Cloud Radiative Effect. Decadal change in this observation is direclty related to the largest uncertainty in climate sensitivity which is cloud feedback from changing amount of low clouds, primarily low clouds over the world's oceans. As a result, decadal changes in shortwave cloud radiative forcing are more directly related to cloud feedback uncertainty which is the dominant uncertainty in climate sensitivity. This paper will show results for the new approach, and allow an examination of the sensitivity of economic value results to different observations used as a constraint on uncertainty in climate sensitivity. The analysis suggests roughly a doubling of economic value to 20 Trillion Net Present Value or Real Option Value at 3% discount rate. The higher economic value results from two changes: a larger increase in accuracy for SW cloud radiative forcing vs temperature, and from a lower confounding noise from natural variability in the cloud radiative forcing variable compared to temperature. In particular, global average temperature is much more sensitive to the climate noise of ENSO cycles.

Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations

PubMed Central

Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao

2017-01-01

A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10–0.20 m, and vertical accuracy was approximately 0.01–0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed. PMID:28398256

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

Martin, Shawn

This code consists of Matlab routines which enable the user to perform non-manifold surface reconstruction via triangulation from high dimensional point cloud data. The code was based on an algorithm originally developed in [Freedman (2007), An Incremental Algorithm for Reconstruction of Surfaces of Arbitrary Codimension Computational Geometry: Theory and Applications, 36(2):106-116]. This algorithm has been modified to accommodate non-manifold surface according to the work described in [S. Martin and J.-P. Watson (2009), Non-Manifold Surface Reconstruction from High Dimensional Point Cloud DataSAND #5272610].The motivation for developing the code was a point cloud describing the molecular conformation space of cyclooctane (C8H16). Cyclooctanemore » conformation space was represented using points in 72 dimensions (3 coordinates for each molecule). The code was used to triangulate the point cloud and thereby study the geometry and topology of cyclooctane. Futures applications are envisioned for peptides and proteins.« less

Classification of Mobile Laser Scanning Point Clouds from Height Features

NASA Astrophysics Data System (ADS)

Zheng, M.; Lemmens, M.; van Oosterom, P.

2017-09-01

The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (MLS) systems are often the preferred geo-data acquisition method for capturing such scenes. Because MLS systems are mounted on cars or vans they can acquire billions of points of road scenes within a few hours of survey. Manual processing of point clouds is labour intensive and thus time consuming and expensive. Hence, the need for rapid and automated methods for 3D mapping of dense point clouds is growing exponentially. The last five years the research on automated 3D mapping of MLS data has tremendously intensified. In this paper, we present our work on automated classification of MLS point clouds. In the present stage of the research we exploited three features - two height components and one reflectance value, and achieved an overall accuracy of 73 %, which is really encouraging for further refining our approach.

Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

NASA Astrophysics Data System (ADS)

An, Lu; Guo, Baolong

2018-03-01

Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).

Observations of Martian ice clouds by the Mars Global Surveyor Thermal Emission Spectrometer: The first Martian year

NASA Astrophysics Data System (ADS)

Pearl, John C.; Smith, Michael D.; Conrath, Barney J.; Bandfield, Joshua L.; Christensen, Philip R.

2001-06-01

Successful operation of the Mars Global Surveyor spacecraft, beginning in September 1997 (Ls=184°), has permitted extensive observations over more than a Martian year. Initially, thin (normal optical depth <0.06 at 825 cm-1) ice clouds and hazes were widespread, showing a distinct latitudinal gradient. With the onset of a regional dust storm at Ls=224°, ice clouds vanished in the southern hemisphere, to reappear gradually after the decay of the storm. The zonally averaged cloud opacities show little difference between the beginning and end of the first Martian year. A broad low-latitude cloud belt with considerable longitudinal structure was present in early northern summer. Apparently characteristic of the northern summer season, it vanished between Ls=140° and 150°. The latitudinal extent of this feature is apparently controlled by the ascending branch of the Hadley circulation. The most opaque clouds (optical depth ~0.6) were found above the summits of major volcanic features; these showed spatial structure possibly associated with wave activity. Variety among low-lying late morning clouds suggests localized differences in circulation and microclimates. Limb observations showed extensive optically thin (optical depth <0.04) stratiform clouds at altitudes up to 55 km. Considerable latitude and altitude variations were evident in ice clouds in early northern spring (Ls=25°) near 30 km, thin clouds extended from just north of the equator to ~45°N, nearly to the north polar vortex. A water ice haze was present in the north polar night (Ls=30°) at altitudes up to 40 km. Because little dust was present this probably provided heterogeneous nucleation sites for the formation of CO2 clouds and snowfall at altitudes below ~20 km, where atmospheric temperatures dropped to the CO2 condensation point. The relatively invariant spectral shape of the water ice cloud feature over space and time indicates that ice particle radii are generally between 1 and 4 μm.

Ice Nucleation in the Tropical Tropopause Layer: Implications for Cirrus Occurrence, Cirrus Microphysical Properties, and Dehydration of Air Entering the Stratosphere

NASA Technical Reports Server (NTRS)

Jensen, Eric; Kaercher, Bernd; Ueyama, Rei; Pfister, Leonhard

2017-01-01

Recent laboratory experiments have advanced our understanding of the physical properties and ice nucleating abilities of aerosol particles atlow temperatures. In particular, aerosols containing organics will transition to a glassy state at low temperatures, and these glassy aerosols are moderately effective as ice nuclei. These results have implications for ice nucleation in the cold Tropical Tropopause Layer (TTL; 13-19 km). We have developed a detailed cloud microphysical model that includes heterogeneous nucleation on a variety of aerosol types and homogeneous freezing of aqueous aerosols. This model has been incorporated into one-dimensional simulations of cirrus and water vapor driven by meteorological analysis temperature and wind fields. The model includes scavenging of ice nuclei by sedimenting ice crystals. The model is evaluated by comparing the simulated cloud properties and water vapor concentrations with aircraft and satellite measurements. In this presentation, I will discuss the relative importance of homogeneous and heterogeneous ice nucleation, the impact of ice nuclei scavenging as air slowly ascends through the TTL, and the implications for the final dehydration of air parcels crossing the tropical cold-point tropopause and entering the tropical stratosphere.

The effect of temperature mixing on the observable (T, β)-relation of interstellar dust clouds

NASA Astrophysics Data System (ADS)

Juvela, M.; Ysard, N.

2012-03-01

Context. Detailed studies of the shape of dust emission spectra are possible thanks to the current instruments capable of simultaneous observations in several sub-millimetre bands (e.g., Herschel and Planck). The relationship between the observed spectra and the intrinsic dust grain properties is known to be affected by the noise and the line-of-sight temperature variations. However, some controversy remains even on the basic effects resulting from the mixing of temperatures along the line-of-sight or within the instrument beam. Aims: Regarding the effect of temperature variations, previous studies have suggested either a positive or a negative correlation between the colour temperature TC and the observed spectral index βObs. Our aim is to show that both cases are possible and to determine the principal factors leading to either behaviour. Methods: We start by studying the behaviour of the sum of two or three modified black bodies at different temperatures. Then, with radiative transfer models of spherical clouds, we examine the probability distributions of the dust mass as a function of the physical dust temperature. With these results as a guideline, we examine the (TC, βobs) relations for different sets of clouds. Results: Even in the simple case of models consisting of two blackbodies at temperatures T0 and T0 + ΔT0, the correlation between TC and βobs can be either positive or negative. If one compares models where the temperature difference ΔT0 between the two blackbodies is varied, the correlation is negative. If the models differ in their mean temperature T0 rather than in ΔT0, the correlation remains positive. Radiative transfer models show that externally heated clouds have different mean temperatures but the widths of their temperature distributions are rather similar. Thus, in observations of samples of such clouds the correlation between TC and βObs is expected to be positive. The same result applies to clouds illuminated by external radiation fields of different intensity. For internally heated clouds a negative correlation is the more likely alternative. Conclusions: Previous studies of the (TC,β) relation have been correct in that, depending on the cloud sample, both positive and negative correlations are possible. For externally heated clouds the effect is opposite to the negative correlation seen in the observations. If the signal-to-noise ratio is high, the observed negative correlation could be explained by the temperature dependence of the dust optical properties but that intrinsic dependence could be even steeper than the observed one.

Spatial Correlations of Anomaly Time Series of AIRS Version-6 Land Surface Skin Temperatures with the Nino-4 Index

NASA Technical Reports Server (NTRS)

Susskind, Joel; Lee, Jae N.; Iredell, Lena

2013-01-01

The AIRS Science Team Version-6 data set is a valuable resource for meteorological studies. Quality Controlled earth's surface skin temperatures are produced on a 45 km x 45 km spatial scale under most cloud cover conditions. The same retrieval algorithm is used for all surface types under all conditions. This study used eleven years of AIRS monthly mean surface skin temperature and cloud cover products to show that land surface skin temperatures have decreased significantly in some areas and increased significantly in other areas over the period September 2002 through August 2013. These changes occurred primarily at 1:30 PM but not at 1:30 AM. Cooling land areas contained corresponding increases in cloud cover over this time period, with the reverse being true for warming land areas. The cloud cover anomaly patterns for a given month are affected significantly by El Nino/La Nina activity, and anomalies in cloud cover are a driving force behind anomalies in land surface skin temperature.

Response to "The Iris Hypothesis: A Negative or Positive Cloud Feedback?"

NASA Technical Reports Server (NTRS)

Chou, Ming-Dah; Lindzen, Richard S.; Hou, Arthur Y.; Lau, William K. M. (Technical Monitor)

2001-01-01

Based on radiance measurements of Japan's Geostationary Meteorological Satellite, Lindzen et al. found that the high-level cloud cover averaged over the tropical western Pacific decreases with increasing sea surface temperature. They further found that the response of high-level clouds to the sea surface temperature had an effect of reducing the magnitude of climate change, which is referred as a negative climate feedback. Lin et al. reassessed the results found by Lindzen et al. by analyzing the radiation and clouds derived from the Tropical Rainfall Measuring Mission Clouds and the Earth's Radiant Energy System measurements. They found a weak positive feedback between high-level clouds and the surface temperature. We have found that the approach taken by Lin et al. to estimating the albedo and the outgoing longwave radiation is incorrect and that the inferred climate sensitivity is unreliable.

Complementary experimental-simulational study of surfactant micellar phase in the extraction process of metallic ions: Effects of temperature and salt concentration

NASA Astrophysics Data System (ADS)

Soto-Ángeles, Alan Gustavo; Rodríguez-Hidalgo, María del Rosario; Soto-Figueroa, César; Vicente, Luis

2018-02-01

The thermoresponsive micellar phase behaviour that exhibits the Triton-X-100 micelles by temperature effect and addition of salt in the extraction process of metallic ions was explored from mesoscopic and experimental points. In the theoretical study, we analyse the formation of Triton-X-100 micelles, load and stabilization of dithizone molecules and metallic ions extraction inside the micellar core at room temperature; finally, a thermal analysis is presented. In the experimental study, the spectrophotometric outcomes confirm the solubility of the copper-dithizone complex in the micellar core, as well as the extraction of metallic ions of aqueous environment via a cloud-point at 332.2 K. The micellar solutions with salt present a low absorbance value compared with the micellar solutions without salt. The decrease in the absorbance value is attributed to a change in the size of hydrophobic region of colloidal micelles. All transitory stages of extraction process are discussed and analysed in this document.

Bio-lubricants derived from waste cooking oil with improved oxidation stability and low-temperature properties.

PubMed

Li, Weimin; Wang, Xiaobo

2015-01-01

Waste cooking oil (WCO) was chemically modified via epoxidation using H2O2 followed by transesterification with methanol and branched alcohols (isooctanol, isotridecanol and isooctadecanol) to produce bio-lubricants with improved oxidative stability and low temperature properties. Physicochemical properties of synthesized bio-lubricants such as pour point (PP), cloud point (CP), viscosity, viscosity index (VI), oxidative stability, and corrosion resistant property were determined according to standard methods. The synthesized bio-lubricants showed improved low temperature flow performances compared with WCO, which can be attributing to the introduction of branched chains in their molecular structures. What's more, the oxidation stability of the WCO showed more than 10 folds improvement due to the elimination of -C=C-bonds in the WCO molecule. Tribological performances of these bio-lubricants were also investigated using four-ball friction and wear tester. Experimental results showed that derivatives of WCO exhibited favorable physicochemical properties and tribological performances which making them good candidates in formulating eco-friendly lubricants.

Effect of electromagnetic field on Kordylewski clouds formation

NASA Astrophysics Data System (ADS)

Salnikova, Tatiana; Stepanov, Sergey

2018-05-01

In previous papers the authors suggest a clarification of the phenomenon of appearance-disappearance of Kordylewski clouds - accumulation of cosmic dust mass in the vicinity of the triangle libration points of the Earth-Moon system. Under gravi-tational and light perturbation of the Sun the triangle libration points aren't the points of relative equilibrium. However, there exist the stable periodic motion of the particles, surrounding every of the triangle libration points. Due to this fact we can consider a probabilistic model of the dust clouds formation. These clouds move along the periodical orbits in small vicinity of the point of periodical orbit. To continue this research we suggest a mathematical model to investigate also the electromagnetic influences, arising under consideration of the charged dust particles in the vicinity of the triangle libration points of the Earth-Moon system. In this model we take under consideration the self-unduced force field within the set of charged particles, the probability distribution density evolves according to the Vlasov equation.

Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

NASA Astrophysics Data System (ADS)

Collins, Patrick; Bahr, Thomas

2016-04-01

The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of the DEM difference to analyze the surface changes in 3D. The automated point cloud generation and analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the point cloud processing tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study allow a 3D estimation of the topographic changes within the tectonically active and anthropogenically invaded Malin area after the landslide event. Accordingly, the point cloud analysis was correlated successfully with modelled displacement contours of the slope. Based on optical satellite imagery, such point clouds of high precision and density distribution can be obtained in a few minutes to support the operational monitoring of landslide processes.

Observations of the boundary layer, cloud, and aerosol variability in the southeast Pacific coastal marine stratocumulus during VOCALS-REx

NASA Astrophysics Data System (ADS)

Zheng, X.; Albrecht, B.; Jonsson, H. H.; Khelif, D.; Feingold, G.; Minnis, P.; Ayers, K.; Chuang, P.; Donaher, S.; Rossiter, D.; Ghate, V.; Ruiz-Plancarte, J.; Sun-Mack, S.

2011-05-01

Aircraft observations made off the coast of northern Chile in the Southeastern Pacific (20° S, 72° W; named Point Alpha) from 16 October to 13 November 2008 during the VAMOS Ocean-Cloud-Atmosphere-Land Study-Regional Experiment (VOCALS-REx), combined with meteorological reanalysis, satellite measurements, and radiosonde data, are used to investigate the boundary layer (BL) and aerosol-cloud-drizzle variations in this region. The BL at Point Alpha was typical of a non-drizzling stratocumulus-topped BL on days without predominately synoptic and meso-scale influences. The BL had a depth of 1140 ± 120 m, was well-mixed and capped by a sharp inversion. The wind direction generally switched from southerly within the BL to northerly above the inversion. The cloud liquid water path (LWP) varied between 15 g m-2 and 160 g m-2. From 29 October to 4 November, when a synoptic system affected conditions at Point Alpha, the cloud LWP was higher than on the other days by around 40 g m-2. On 1 and 2 November, a moist layer above the inversion moved over Point Alpha. The total-water specific humidity above the inversion was larger than that within the BL during these days. Entrainment rates (average of 1.5 ± 0.6 mm s-1) calculated from the near cloud-top fluxes and turbulence (vertical velocity variance) in the BL at Point Alpha appeared to be weaker than those in the BL over the open ocean west of Point Alpha and the BL near the coast of the northeast Pacific. The accumulation mode aerosol varied from 250 to 700 cm-3 within the BL, and CCN at 0.2 % supersaturation within the BL ranged between 150 and 550 cm-3. The main aerosol source at Point Alpha was horizontal advection within the BL from south. The average cloud droplet number concentration ranged between 80 and 400 cm-3, which was consistent with the satellite-derived values. The relationship of cloud droplet number concentration and CCN at 0.2 % supersaturation from 18 flights is Nd =4.6 × CCN0.71. While the mean LWP retrieved from GOES was in good agreement with the in situ measurements, the GOES-derived cloud droplet effective radius tended to be larger than that from the aircraft {in situ} observations near cloud top. The aerosol and cloud LWP relationship reveals that during the typical well-mixed BL days the cloud LWP increased with the CCN concentrations. On the other hand, meteorological factors and the decoupling processes have large influences on the cloud LWP variation as well.

Geo-spatial distribution of cloud cover and influence of cloud induced attenuation and noise temperature on satellite signal propagation over Nigeria

NASA Astrophysics Data System (ADS)

Ojo, Joseph Sunday

2017-05-01

The study of the influence of cloud cover on satellite propagation links is becoming more demanding due to the requirement of larger bandwidth for different satellite applications. Cloud attenuation is one of the major factors to consider for optimum performance of Ka/V and other higher frequency bands. In this paper, the geo-spatial distribution of cloud coverage over some chosen stations in Nigeria has been considered. The substantial scale spatial dispersion of cloud cover based on synoptic meteorological data and the possible impact on satellite communication links at higher frequency bands was also investigated. The investigation was based on 5 years (2008-2012) achieved cloud cover data collected by the Nigerian Meteorological Agency (NIMET) Federal Ministry of Aviation, Oshodi Lagos over four synoptic hours of the day covering day and night. The performances of satellite signals as they traverse through the cloud and cloud noise temperature at different seasons and over different hours of days at Ku/W-bands frequency are also examined. The overall result shows that the additional total atmospheric noise temperature due to the clear air effect and the noise temperature from the cloud reduces the signal-to-noise ratio of the satellite receiver systems, leading to more signal loss and if not adequately taken care of may lead to significant outage. The present results will be useful for Earth-space link budgeting, especially for the proposed multi-sensors communication satellite systems in Nigeria.

Investigation of tropical cirrus cloud properties using ground based lidar measurements

NASA Astrophysics Data System (ADS)

Dhaman, Reji K.; Satyanarayana, Malladi; Krishnakumar, V.; Mahadevan Pillai, V. P.; Jayeshlal, G. S.; Raghunath, K.; Venkat Ratnam, M.

2016-05-01

Cirrus clouds play a significant role in the Earths radiation budget. Therefore, knowledge of geometrical and optical properties of cirrus cloud is essential for the climate modeling. In this paper, the cirrus clouds microphysical and optical properties are made by using a ground based lidar measurements over an inland tropical station Gadanki (13.5°N, 79.2°E), Andhra Pradesh, India. The variation of cirrus microphysical and optical properties with mid cloud temperature is also studied. The cirrus clouds mean height is generally observed in the range of 9-17km with a peak occurrence at 13- 14km. The cirrus mid cloud temperature ranges from -81°C to -46°C. The cirrus geometrical thickness ranges from 0.9- 4.5km. During the cirrus occurrence days sub-visual, thin and dense cirrus were at 37.5%, 50% and 12.5% respectively. The monthly cirrus optical depth ranges from 0.01-0.47, but most (<80%) of the cirrus have values less than 0.1. Optical depth shows a strong dependence with cirrus geometrical thickness and mid-cloud height. The monthly mean cirrus extinction ranges from 2.8E-06 to 8E-05 and depolarization ratio and lidar ratio varies from 0.13 to 0.77 and 2 to 52 sr respectively. A positive correlation exists for both optical depth and extinction with the mid-cloud temperature. The lidar ratio shows a scattered behavior with mid-cloud temperature.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

Weiss, Mitchell; Smith, Eric A.

1987-06-01

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

Using regime analysis to identify the contribution of clouds to surface temperature errors in weather and climate models

DOE PAGES

Van Weverberg, Kwinten; Morcrette, Cyril J.; Ma, Hsi -Yen; ...

2015-06-17

Many global circulation models (GCMs) exhibit a persistent bias in the 2 m temperature over the midlatitude continents, present in short-range forecasts as well as long-term climate simulations. A number of hypotheses have been proposed, revolving around deficiencies in the soil–vegetation–atmosphere energy exchange, poorly resolved low-level boundary-layer clouds or misrepresentations of deep-convective storms. A common approach to evaluating model biases focuses on the model-mean state. However, this makes difficult an unambiguous interpretation of the origins of a bias, given that biases are the result of the superposition of impacts of clouds and land-surface deficiencies over multiple time steps. This articlemore » presents a new methodology to objectively detect the role of clouds in the creation of a surface warm bias. A unique feature of this study is its focus on temperature-error growth at the time-step level. It is shown that compositing the temperature-error growth by the coinciding bias in total downwelling radiation provides unambiguous evidence for the role that clouds play in the creation of the surface warm bias during certain portions of the day. Furthermore, the application of an objective cloud-regime classification allows for the detection of the specific cloud regimes that matter most for the creation of the bias. We applied this method to two state-of-the-art GCMs that exhibit a distinct warm bias over the Southern Great Plains of the USA. Our analysis highlights that, in one GCM, biases in deep-convective and low-level clouds contribute most to the temperature-error growth in the afternoon and evening respectively. In the second GCM, deep clouds persist too long in the evening, leading to a growth of the temperature bias. In conclusion, the reduction of the temperature bias in both models in the morning and the growth of the bias in the second GCM in the afternoon could not be assigned to a cloud issue, but are more likely caused by a land-surface deficiency.« less

Cloud tolerance of remote sensing technologies to measure land surface temperature

USDA-ARS?s Scientific Manuscript database

Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

Particle size distribution properties in mixed-phase monsoon clouds from in situ measurements during CAIPEEX

NASA Astrophysics Data System (ADS)

Patade, Sachin; Prabha, T. V.; Axisa, D.; Gayatri, K.; Heymsfield, A.

2015-10-01

A comprehensive analysis of particle size distributions measured in situ with airborne instrumentation during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) is presented. In situ airborne observations in the developing stage of continental convective clouds during premonsoon (PRE), transition, and monsoon (MON) period at temperatures from 25 to -22°C are used in the study. The PRE clouds have narrow drop size and particle size distributions compared to monsoon clouds and showed less development of size spectra with decrease in temperature. Overall, the PRE cases had much lower values of particle number concentrations and ice water content compared to MON cases, indicating large differences in the ice initiation and growth processes between these cloud regimes. This study provided compelling evidence that in addition to dynamics, aerosol and moisture are important for modulating ice microphysical processes in PRE and MON clouds through impacts on cloud drop size distribution. Significant differences are observed in the relationship of the slope and intercept parameters of the fitted particle size distributions (PSDs) with temperature in PRE and MON clouds. The intercept values are higher in MON clouds than PRE for exponential distribution which can be attributed to higher cloud particle number concentrations and ice water content in MON clouds. The PRE clouds tend to have larger values of dispersion of gamma size distributions than MON clouds, signifying narrower spectra. The relationships between PSDs parameters are presented and compared with previous observations.

Relationship between cloud-to-ground discharge and penetrative clouds: A multi-channel satellite application

NASA Astrophysics Data System (ADS)

Machado, Luiz A. T.; Lima, Wagner F. A.; Pinto, Osmar; Morales, Carlos A.

This work presents a relationship between atmospheric cloud-to-ground discharges and penetrative convective clouds. It combines Infrared and Water Vapor channels from the GOES-12 geostationary satellite with cloud-to-ground discharge data from the Brazilian Integrated Lightning Detection Network (RINDAT) during the period from January to February 2005. The difference between water vapor and infrared brightness temperature is a tracer penetrating clouds. Due to the water vapor channel's strong absorption, this difference is positive only during overshooting cases, when convective clouds penetrate the stratosphere. From this difference and the cloud-to-ground, discharge measured on the ground by RINDAT, it was possible to adjust exponential curves that relate the brightness temperature difference from these two channels to the probability of occurrence of cloud-to-ground discharges, with a very large coefficient of determination. If WV-IR brightness temperature difference is greater than - 15 K there is a large potential for cloud-to-ground discharge activity. As this difference increases the cloud-to-ground discharge probably increases, for example: if this difference is equal to zero, the probability of having at least one cloud-to-ground discharge is 10.9%, 7.0% for two, 4.4% for four, 2.7% for eight and 1.5% for sixteen cloud-to-ground discharges. Through this process, was developed a scheme that estimates the probability of occurrence of cloud-to-ground discharge over all the continental region of South America.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

PubMed Central

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-01-01

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

PubMed

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-12-24

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

Meteorological Drivers of Cold Temperatures in the Western Pacific TTL

NASA Technical Reports Server (NTRS)

Pfister, Leonhard; Ueyama, Rei; Jensen, Eric J.

2017-01-01

During the recent October 2016 aircraft sampling mission of the Tropical Tropopause Layer (POSIDON -- Pacific Oxidants, Sulfur, Ice, Dehydration, and cONvection), Western Pacific October TTL temperatures were anomalously cold due to a combination of La Nina conditions and a very stationary convective pattern. POSIDON also had more October Tropical Cyclones than typical, and tropical cyclones have substantial negative TTL temperatures associated with them. This paper investigates how meteorology in the troposphere drives TTL temperatures, and how these temperatures, coupled with the circulation, produce TTL clouds. We will also compare October TTL cloud distributions in different years, examining the relationship of clouds to October temperature anomalies.

Tropical Depression Debbie in the Atlantic

NASA Image and Video Library

2006-08-22

These images show Tropical Depression Debbie in the Atlantic, from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on August 22, 2006. This AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the storm. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). At the time the data were taken from which these images were made the eye had not yet opened but the storm is now well organized. The location of the future eye appears as a circle at 275 K brightness temperature in the microwave image just to the SE of the Azores. http://photojournal.jpl.nasa.gov/catalog/PIA00508

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

NASA Astrophysics Data System (ADS)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the displacement fields. Displacement fields derived from both approaches are then combined and provide a better understanding of the landslide kinematics.

Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

Intensification of convective extremes driven by cloud-cloud interaction

NASA Astrophysics Data System (ADS)

Moseley, Christopher; Hohenegger, Cathy; Berg, Peter; Haerter, Jan O.

2016-10-01

In a changing climate, a key role may be played by the response of convective-type cloud and precipitation to temperature changes. Yet, it is unclear if convective precipitation intensities will increase mainly due to thermodynamic or dynamical processes. Here we perform large eddy simulations of convection by imposing a realistic diurnal cycle of surface temperature. We find convective events to gradually self-organize into larger cloud clusters and those events occurring late in the day to produce the highest precipitation intensities. Tracking rain cells throughout their life cycles, we show that events which result from collisions respond strongly to changes in boundary conditions, such as temperature changes. Conversely, events not resulting from collisions remain largely unaffected by the boundary conditions. Increased surface temperature indeed leads to more interaction between events and stronger precipitation extremes. However, comparable intensification occurs when leaving temperature unchanged but simply granting more time for self-organization. These findings imply that the convective field as a whole acquires a memory of past precipitation and inter-cloud dynamics, driving extremes. For global climate model projections, our results suggest that the interaction between convective clouds must be incorporated to simulate convective extremes and the diurnal cycle more realistically.

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

NASA Astrophysics Data System (ADS)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

Synthesis of biodiesel fuel from safflower oil using various reaction parameters.

PubMed

Meka, Pavan Kumar; Tripathi, Vinay; Singh, R P

2006-01-01

Biodiesel fuel is gaining more and more importance because of the depletion and uncontrollable prices of fossil fuel resources. The use of vegetable oil and their derivatives as alternatives for diesel fuel is the best answer and as old as Diesel Engine. Chemically biodiesel fuel is the mono alkyl esters of fatty acids derived from renewable feed stocks like vegetable oils and animal fats. Safflower oil contains 75-80% of linoleic acid; the presence of this unsaturated fatty acid is useful in alleviating low temperature properties like pour point, cloud point and cold filter plugging point. In this paper we studied the effect of various parameters such as temperature, molar ratio (oil to alcohol), and concentration of catalyst on synthesis of biodiesel fuel from safflower oil. The better suitable conditions of 1:6 molar ratio (oil to alcohol), 60 degrees C temperature and catalyst concentration of 2% (by wt. of oil) were determined. The finally obtained biodiesel fuel was analyzed for fatty acid composition by GLC and some other properties such as flash point, specific gravity and acid value were also determined. From the results it was clear that the produced biodiesel fuel was with in the recommended standards of biodiesel fuel with 96.8% yield.

Transport of infrared radiation in cuboidal clouds

NASA Technical Reports Server (NTRS)

HARSHVARDHAN; Weinman, J. A.; Davies, R.

1981-01-01

The transport of infrared radiation in a single cuboidal cloud using a vertical two steam approximation was modeled. The emittance of the top face of the model cloud is always less than that for a plane parallel cloud of the same optical depth. The hemisphere flux escaping from the cloud top has a gradient from the center to the edges which brighten when the cloud is over warmer ground. Cooling rate calculations in the 8 to 13.6 micrometer region show that there is cooling from the sides of the cloud at all levels even when there is heating of the core from the ground below. The radiances exiting from model cuboidal clouds were computed by path integration over the source function obtained with the two stream approximation. It is suggested that the brightness temperature measured from finite clouds will overestimate the cloud top temperature.

Street curb recognition in 3d point cloud data using morphological operations

NASA Astrophysics Data System (ADS)

Rodríguez-Cuenca, Borja; Concepción Alonso-Rodríguez, María; García-Cortés, Silverio; Ordóñez, Celestino

2015-04-01

Accurate and automatic detection of cartographic-entities saves a great deal of time and money when creating and updating cartographic databases. The current trend in remote sensing feature extraction is to develop methods that are as automatic as possible. The aim is to develop algorithms that can obtain accurate results with the least possible human intervention in the process. Non-manual curb detection is an important issue in road maintenance, 3D urban modeling, and autonomous navigation fields. This paper is focused on the semi-automatic recognition of curbs and street boundaries using a 3D point cloud registered by a mobile laser scanner (MLS) system. This work is divided into four steps. First, a coordinate system transformation is carried out, moving from a global coordinate system to a local one. After that and in order to simplify the calculations involved in the procedure, a rasterization based on the projection of the measured point cloud on the XY plane was carried out, passing from the 3D original data to a 2D image. To determine the location of curbs in the image, different image processing techniques such as thresholding and morphological operations were applied. Finally, the upper and lower edges of curbs are detected by an unsupervised classification algorithm on the curvature and roughness of the points that represent curbs. The proposed method is valid in both straight and curved road sections and applicable both to laser scanner and stereo vision 3D data due to the independence of its scanning geometry. This method has been successfully tested with two datasets measured by different sensors. The first dataset corresponds to a point cloud measured by a TOPCON sensor in the Spanish town of Cudillero. That point cloud comprises more than 6,000,000 points and covers a 400-meter street. The second dataset corresponds to a point cloud measured by a RIEGL sensor in the Austrian town of Horn. That point cloud comprises 8,000,000 points and represents a 160-meter street. The proposed method provides success rates in curb recognition of over 85% in both datasets.

New particle dependant parameterizations of heterogeneous freezing processes.

NASA Astrophysics Data System (ADS)

Diehl, Karoline; Mitra, Subir K.

2014-05-01

For detailed investigations of cloud microphysical processes an adiabatic air parcel model with entrainment is used. It represents a spectral bin model which explicitly solves the microphysical equations. The initiation of the ice phase is parameterized and describes the effects of different types of ice nuclei (mineral dust, soot, biological particles) in immersion, contact, and deposition modes. As part of the research group INUIT (Ice Nuclei research UnIT), existing parameterizations have been modified for the present studies and new parameterizations have been developed mainly on the basis of the outcome of INUIT experiments. Deposition freezing in the model is dependant on the presence of dry particles and on ice supersaturation. The description of contact freezing combines the collision kernel of dry particles with the fraction of frozen drops as function of temperature and particle size. A new parameterization of immersion freezing has been coupled to the mass of insoluble particles contained in the drops using measured numbers of ice active sites per unit mass. Sensitivity studies have been performed with a convective temperature and dew point profile and with two dry aerosol particle number size distributions. Single and coupled freezing processes are studied with different types of ice nuclei (e.g., bacteria, illite, kaolinite, feldspar). The strength of convection is varied so that the simulated cloud reaches different levels of temperature. As a parameter to evaluate the results the ice water fraction is selected which is defined as the relation of the ice water content to the total water content. Ice water fractions between 0.1 and 0.9 represent mixed-phase clouds, larger than 0.9 ice clouds. The results indicate the sensitive parameters for the formation of mixed-phase and ice clouds are: 1. broad particle number size distribution with high number of small particles, 2. temperatures below -25°C, 3. specific mineral dust particles as ice nuclei such as illite or montmorillonite. Coupled cases of deposition and contact freezing show that they are hardly in competition because of differences in the preferred particle sizes. In the contact mode, small particles are less efficient for collisions as well as less efficient as ice nuclei so that these are available for deposition freezing. On the other hand, immersion freezing is the dominant process when it is coupled with deposition freezing. As it is initiated earlier the formed ice particles consume water vapor for growing. The competition of combined contact and immersion freezing leads to lower ice water contents because more ice particles are formed via the immersion mode. In general, ice clouds and mixed-phase clouds with high ice water fractions are not directly the result of primary ice formation but of secondary ice formation and growth of ice particles at the expense of liquid drops.

3D reconstruction from non-uniform point clouds via local hierarchical clustering

NASA Astrophysics Data System (ADS)

Yang, Jiaqi; Li, Ruibo; Xiao, Yang; Cao, Zhiguo

2017-07-01

Raw scanned 3D point clouds are usually irregularly distributed due to the essential shortcomings of laser sensors, which therefore poses a great challenge for high-quality 3D surface reconstruction. This paper tackles this problem by proposing a local hierarchical clustering (LHC) method to improve the consistency of point distribution. Specifically, LHC consists of two steps: 1) adaptive octree-based decomposition of 3D space, and 2) hierarchical clustering. The former aims at reducing the computational complexity and the latter transforms the non-uniform point set into uniform one. Experimental results on real-world scanned point clouds validate the effectiveness of our method from both qualitative and quantitative aspects.

Deadly Fires Engulfing Madeira seen by NASA MISR

NASA Image and Video Library

2016-08-12

A wildfire spread to the capital city of Funchal on the island of Madeira, an autonomous region of Portugal, over the nighttime hours of Tuesday, Aug. 9, 2016, with three deaths reported and hundreds of others hospitalized. Several homes and a luxury hotel have burned, and a thousand people have been evacuated. The three fatalities are reported to be elderly people who were unable to escape when their homes caught fire. The fire ignited Monday, Aug. 8, after several weeks of scorching temperatures topping 95 degrees Fahrenheit and very dry weather. The entire island is only 30 miles (48 kilometers) from end to end, which naturally makes protecting the island's 270,000 residents and many tourists more difficult. The MISR (Multi-angle Imaging SpectroRadiometer) instrument aboard NASA's Terra satellite passed directly over the island of Madeira on Wednesday, Aug. 10, 2016. The left image is a true-color image taken by MISR's 60-degree forward-pointing camera. This oblique view gives a better view of the smoke than a downward-pointing view. The island of Madeira is the only land within the field of view, and the smoke from the wildfire is being blown to the southwest. The city of Funchal is located on the southeastern coast of the island. MISR's nine cameras, each viewing Earth at a different angle, can be used to determine the height of clouds and smoke above the surface in much the same way that our two eyes, pointing in slightly different directions, give us depth perception. The right-hand image shows MISR's publically available standard cloud top height product. These data show that the main body of clouds is indeed very low, less than 0.6 miles (1 kilometer) above sea level, while the smoke plume is about 1.9 miles (3 kilometers) high at the source, dropping lower as it is blown to the southwest. A stereo "anaglyph" of this scene is also available at PIA20886. As can be seen from both the MISR height product and the 3D anaglyph, the isolated clouds to the south are much higher than either the low clouds or the plume. Interestingly, the low clouds drop to almost sea level and then die out near where the smoke is present. These data were acquired during Terra orbit 88524. http://photojournal.jpl.nasa.gov/catalog/PIA20887

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Applications of low altitude photogrammetry for morphometry, displacements, and landform modeling

NASA Astrophysics Data System (ADS)

Gomez, F. G.; Polun, S. G.; Hickcox, K.; Miles, C.; Delisle, C.; Beem, J. R.

2016-12-01

Low-altitude aerial surveying is emerging as a tool that greatly improves the ease and efficiency of measuring landforms for quantitative geomorphic analyses. High-resolution, close-range photogrammetry produces dense, 3-dimensional point clouds that facilitate the construction of digital surface models, as well as a potential means of classifying ground targets using spatial structure. This study presents results from recent applications of UAS-based photogrammetry, including high resolution surface morphometry of a lava flow, repeat-pass applications to mass movements, and fault scarp degradation modeling. Depending upon the desired photographic resolution and the platform/payload flown, aerial photos are typically acquired at altitudes of 40 - 100 meters above the ground surface. In all cases, high-precision ground control points are key for accurate (and repeatable) orientation - relying on low-precision GPS coordinates (whether on the ground or geotags in the aerial photos) typically results in substantial rotations (tilt) of the reference frame. Using common ground control points between repeat surveys results in matching point clouds with RMS residuals better than 10 cm. In arid regions, the point cloud is used to assess lava flow surface roughness using multi-scale measurements of point cloud dimensionality. For the landslide study, the point cloud provides a basis for assessing possible displacements. In addition, the high resolution orthophotos facilitate mapping of fractures and their growth. For neotectonic applications, we compare fault scarp modeling results from UAV-derived point clouds versus field-based surveys (kinematic GPS and electronic distance measurements). In summary, there is a wide ranging toolbox of low-altitude aerial platforms becoming available for field geoscientists. In many instances, these tools will present convenience and reduced cost compared with the effort and expense to contract acquisitions of aerial imagery.

SEMANTIC3D.NET: a New Large-Scale Point Cloud Classification Benchmark

NASA Astrophysics Data System (ADS)

Hackel, T.; Savinov, N.; Ladicky, L.; Wegner, J. D.; Schindler, K.; Pollefeys, M.

2017-05-01

This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods. We also discuss first submissions to the benchmark that use deep convolutional neural networks (CNNs) as a work horse, which already show remarkable performance improvements over state-of-the-art. CNNs have become the de-facto standard for many tasks in computer vision and machine learning like semantic segmentation or object detection in images, but have no yet led to a true breakthrough for 3D point cloud labelling tasks due to lack of training data. With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks. Our semantic3D.net data set consists of dense point clouds acquired with static terrestrial laser scanners. It contains 8 semantic classes and covers a wide range of urban outdoor scenes: churches, streets, railroad tracks, squares, villages, soccer fields and castles. We describe our labelling interface and show that our data set provides more dense and complete point clouds with much higher overall number of labelled points compared to those already available to the research community. We further provide baseline method descriptions and comparison between methods submitted to our online system. We hope semantic3D.net will pave the way for deep learning methods in 3D point cloud labelling to learn richer, more general 3D representations, and first submissions after only a few months indicate that this might indeed be the case.

Cloud Radiative Effect to Downward Longwave Radiation in the Polar Regions

NASA Astrophysics Data System (ADS)

Yamada, K.; Hayasaka, T.

2014-12-01

Downward longwave radiation is important factor to affect climate change. In polar regions, estimation of the radiative effect of cloud on the downward longwave radiation has large uncertainty. Relatively large cloud effect to the radiation occurs there due to low temperature, small amount of water vapor, and strong inversion layer. The cloud effect is, however, not evaluated sufficiently because the long term polar night and high surface albedo make satellite retrieval difficult. The intent of the present study is to quantify cloud radiative effect for downward longwave radiation in the polar regions by in-situ observation and radiative transfer calculation. The observation sites in this study are Ny-Ålesund (NYA), Syowa (SYO), and South Pole (SPO). These stations belong to the Baseline Surface Radiation Network. The period of data analysis is from 2003 to 2012. The effect of cloud on the downward longwave radiation is evaluated by subtraction of calculated downward longwave radiation under clear-sky condition from observed value under all-sky condition. Radiative transfer model was used for the evaluation of clear sky radiation with vertical temperature and humidity profile obtained by radiosonde observations. Calculated result shows good correlation with observation under clear-sky condition. The RMSE is +0.83±5.0. The cloud effect varied from -10 - +110 W/m2 (-10 - +40 %). Cloud effect increased with increasing of cloud fraction and decreasing of cloud base height and precipitable water. In SYO negative effects were sometimes obtained. The negative cloud effect emerged under dry and temperature inversion condition lower than 2 km. One of reasons of negative effect is considered to be existence of cloud at temperature inversion altitude. When the cloud effect is smaller than -5 W/m2 (standard deviation between calculation and observation), 50 % of them have a condition with cloud base height estimated by micro pulse lidar lower than 2 km.

The CREW intercomparison of SEVIRI cloud retrievals

NASA Astrophysics Data System (ADS)

Hamann, U.; Walther, A.; Bennartz, R.; Thoss, A.; Meirink, J. M.; Roebeling, R.

2012-12-01

About 70% of the earth's surface is covered with clouds. They strongly influence the radiation balance and the water cycle of the earth. Hence the detailed monitoring of cloud properties - such as cloud fraction, cloud top temperature, cloud particle size, and cloud water path - is important to understand the role of clouds in the weather and the climate system. The remote sensing with passive sensors is an essential mean for the global observation of the cloud parameters, but is nevertheless challenging. This presentation focuses on the inter-comparison and validation of cloud physical properties retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard METEOSAT. For this study we use retrievals from 12 state-of-art algorithms (Eumetsat, KNMI, NASA Langley, NASA Goddard, University Madison/Wisconsin, DWD, DLR, Meteo-France, KMI, FU Berlin, UK MetOffice) that are made available through the common database of the CREW (Cloud Retrieval Evaluation Working) group. Cloud detection, cloud top phase, height, and temperature, as well as optical properties and water path are validated with CLOUDSAT, CALIPSO, MISR, and AMSR-E measurements. Special emphasis is given to challenging retrieval conditions. Semi-transparent clouds over the earth's surface or another cloud layer modify the measured brightness temperature and increase the retrieval uncertainty. The consideration of the three-dimensional radiative effects is especially important for large viewing angles and broken cloud fields. Aerosols might be misclassified as cloud and may increase the retrieval uncertainty, too. Due to the availability of the high number of sophisticated retrieval datasets, the advantages of different retrieval approaches can be examined and suggestions for future retrieval developments can be made. We like to thank Eumetsat for sponsoring the CREW project including this work.nstitutes that participate in the CREW project.

Incorporation of surface albedo-temperature feedback in a one-dimensional radiative-connective climate model

NASA Technical Reports Server (NTRS)

Wang, W. C.; Stone, P. H.

1979-01-01

The feedback between ice snow albedo and temperature is included in a one dimensional radiative convective climate model. The effect of this feedback on sensitivity to changes in solar constant is studied for the current values of the solar constant and cloud characteristics. The ice snow albedo feedback amplifies global climate sensitivity by 33% and 50%, respectively, for assumptions of constant cloud altitude and constant cloud temperature.

Measuring the Temperature of the Ithaca College MOT Cloud using a CMOS Camera

NASA Astrophysics Data System (ADS)

Smucker, Jonathan; Thompson, Bruce

2015-03-01

We present our work on measuring the temperature of Rubidium atoms cooled using a magneto-optical trap (MOT). The MOT uses laser trapping methods and Doppler cooling to trap and cool Rubidium atoms to form a cloud that is visible to a CMOS Camera. The Rubidium atoms are cooled further using optical molasses cooling after they are released from the trap (by removing the magnetic field). In order to measure the temperature of the MOT we take pictures of the cloud using a CMOS camera as it expands and calculate the temperature based on the free expansion of the cloud. Results from the experiment will be presented along with a summary of the method used.

Mesoscale Features and Cloud Organization on 10-12 December 1978 over the South China Sea.

NASA Astrophysics Data System (ADS)

Warner, Charles

1982-07-01

Aircraft data from Winter MONEX have been combined with other data to study mesoscale features, and organization of cumulus clouds, on 10-12 December 1978. A moderate cold surge in the northeasterly monsoon flow, toward cloudiness in an equatorial trough off Borneo, peaked on 11 December.Clouds in the northeasterly monsoon flow were similar to those in the trades, with variations in convective regime on length scales on the order of 100 km. Marked mid-tropospheric subsidence was accompanied by low-level divergence near 20°N. During 10 December, anvil clouds near Borneo expanded; cumulus congestus and cumulonimbus formed on the periphery of this area. The approach of the low-level northeasterlies to the area of anvils was marked by a diminution of subsidence, conditional instability, and a weak field of low-level convergence, with randomly organized cumulus of increasing height. A low-level easterly jet was found in this transition zone, downstream from cloudiness over the Philippines. South of Vietnam, a clear area was associated with low air temperatures, and not subsidence. Congestus and cumulonimbus clouds formed near the eastern coast of the Malay Peninsula.Cloud streets were seen from latitude 19°N to the Malaysian coast (with a break south of Vietnam). These clouds were confined below the level of an inflection point in the profile of winds normal to the street direction. Greatest spacings of streets occurred with greatest vertical shears of the cross-winds. Cloud number densities were more closely related to the instability of the vertical stratification than to any other parameter.Cross-wind organization of clouds occurred in circumstances of unstable, stratification and apparently of net ascent. Alignment of clouds was at an angle to the directions of both winds and vertical wind shears. It is inferred that when convergence was strong, deep clouds occurred along lines of convergence in the surface streamlines.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Can cloud point-based enrichment, preservation, and detection methods help to bridge gaps in aquatic nanometrology?

PubMed

Duester, Lars; Fabricius, Anne-Lena; Jakobtorweihen, Sven; Philippe, Allan; Weigl, Florian; Wimmer, Andreas; Schuster, Michael; Nazar, Muhammad Faizan

2016-11-01

Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.

An approach of point cloud denoising based on improved bilateral filtering

NASA Astrophysics Data System (ADS)

Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin

2018-04-01

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

Water Ice Cloud Opacities and Temperatures Derived from the Viking IRTM Data Set

NASA Technical Reports Server (NTRS)

TamppariL. K.; Zurek, R. W.; Paige, D. A.

1999-01-01

The degree to which water ice clouds play a role in the Mars climate is unknown. Latent heating of water ice clouds is small and since most hazes appeared to be thin (tau less than or = 1) their radiative effects have been neglected. Condensation likely limits the vertical extent of water vapor in the water column and a lowering of the condensation altitude, as seen in the northern spring and summer, could increase the seasonal exchange of water between the atmosphere and the surface. It has been suggested that water ice cloud formation is more frequent and widespread in the aphelic hemisphere (currently the northern). This may limit water to the northern hemisphere through greater exchange with the regolith and through restricted southward transport of water vapor by the Mars Hadley circulation. In addition, it has been suggested that water ice cloud formation also controls the vertical distribution of atmospheric dust in some seasons. This scavenging of dust may Continuing from the IRTM cloud maps, derived cloud opacities and cloud temperatures for several locations and seasons will be presented. Sensitivities to cloud particle sizes, surface temperature, and dust opacity will be discussed.

Point cloud modeling using the homogeneous transformation for non-cooperative pose estimation

NASA Astrophysics Data System (ADS)

Lim, Tae W.

2015-06-01

A modeling process to simulate point cloud range data that a lidar (light detection and ranging) sensor produces is presented in this paper in order to support the development of non-cooperative pose (relative attitude and position) estimation approaches which will help improve proximity operation capabilities between two adjacent vehicles. The algorithms in the modeling process were based on the homogeneous transformation, which has been employed extensively in robotics and computer graphics, as well as in recently developed pose estimation algorithms. Using a flash lidar in a laboratory testing environment, point cloud data of a test article was simulated and compared against the measured point cloud data. The simulated and measured data sets match closely, validating the modeling process. The modeling capability enables close examination of the characteristics of point cloud images of an object as it undergoes various translational and rotational motions. Relevant characteristics that will be crucial in non-cooperative pose estimation were identified such as shift, shadowing, perspective projection, jagged edges, and differential point cloud density. These characteristics will have to be considered in developing effective non-cooperative pose estimation algorithms. The modeling capability will allow extensive non-cooperative pose estimation performance simulations prior to field testing, saving development cost and providing performance metrics of the pose estimation concepts and algorithms under evaluation. The modeling process also provides "truth" pose of the test objects with respect to the sensor frame so that the pose estimation error can be quantified.

Quality Assessment and Comparison of Smartphone and Leica C10 Laser Scanner Based Point Clouds

NASA Astrophysics Data System (ADS)

Sirmacek, Beril; Lindenbergh, Roderik; Wang, Jinhu

2016-06-01

3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras (which can generate point clouds based on photogrammetry) can provide denser sampling of 3D surface geometry. Unfortunately, terrestrial laser scanning sensors are expensive and trained persons are needed to use them for point cloud acquisition. A potential effective 3D modelling can be generated based on a low cost smartphone sensor. Herein, we show examples of using smartphone camera images to generate 3D models of urban structures. We compare a smartphone based 3D model of an example structure with a terrestrial laser scanning point cloud of the structure. This comparison gives us opportunity to discuss the differences in terms of geometrical correctness, as well as the advantages, disadvantages and limitations in data acquisition and processing. We also discuss how smartphone based point clouds can help to solve further problems with 3D urban model generation in a practical way. We show that terrestrial laser scanning point clouds which do not have color information can be colored using smartphones. The experiments, discussions and scientific findings might be insightful for the future studies in fast, easy and low-cost 3D urban model generation field.

Knowledge-Based Object Detection in Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Boochs, F.; Karmacharya, A.; Marbs, A.

2012-07-01

Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

Roughness Estimation from Point Clouds - A Comparison of Terrestrial Laser Scanning and Image Matching by Unmanned Aerial Vehicle Acquisitions

NASA Astrophysics Data System (ADS)

Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg

2013-04-01

Recently, terrestrial laser scanning (TLS) and matching of images acquired by unmanned arial vehicles (UAV) are operationally used for 3D geodata acquisition in Geoscience applications. However, the two systems cover different application domains in terms of acquisition conditions and data properties i.e. accuracy and line of sight. In this study we investigate the major differences between the two platforms for terrain roughness estimation. Terrain roughness is an important input for various applications such as morphometry studies, geomorphologic mapping, and natural process modeling (e.g. rockfall, avalanche, and hydraulic modeling). Data has been collected simultaneously by TLS using an Optech ILRIS3D and a rotary UAV using an octocopter from twins.nrn for a 900 m² test site located in a riverbed in Tyrol, Austria (Judenbach, Mieming). The TLS point cloud has been acquired from three scan positions. These have been registered using iterative closest point algorithm and a target-based referencing approach. For registration geometric targets (spheres) with a diameter of 20 cm were used. These targets were measured with dGPS for absolute georeferencing. The TLS point cloud has an average point density of 19,000 pts/m², which represents a point spacing of about 5 mm. 15 images where acquired by UAV in a height of 20 m using a calibrated camera with focal length of 18.3 mm. A 3D point cloud containing RGB attributes was derived using APERO/MICMAC software, by a direct georeferencing approach based on the aircraft IMU data. The point cloud is finally co-registered with the TLS data to guarantee an optimal preparation in order to perform the analysis. The UAV point cloud has an average point density of 17,500 pts/m², which represents a point spacing of 7.5 mm. After registration and georeferencing the level of detail of roughness representation in both point clouds have been compared considering elevation differences, roughness and representation of different grain sizes. UAV closes the gap between aerial and terrestrial surveys in terms of resolution and acquisition flexibility. This is also true for the data accuracy. Considering these data collection and data quality properties of both systems they have their merit on its own in terms of scale, data quality, data collection speed and application.

Relating rainfall characteristics to cloud top temperatures at different scales

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Belušić, Danijel; Taylor, Christopher

2017-04-01

Extreme rainfall from mesoscale convective systems (MCS) poses a threat to lives and livelihoods of the West African population through increasingly frequent devastating flooding and loss of crops. However, despite the significant impact of such extreme events, the dominant processes favouring their occurrence are still under debate. In the data-sparse West African region, rainfall radar data from the Tropical Rainfall Measuring Mission (TRMM) gives invaluable information on the distribution and frequency of extreme rainfall. The TRMM 2A25 product provides a 15-year dataset of snapshots of surface rainfall from 2-4 overpasses per day. Whilst this sampling captures the overall rainfall characteristics, it is neither long nor frequent enough to diagnose changes in MCS properties, which may be linked to the trend towards rainfall intensification in the region. On the other hand, Meteosat geostationary satellites provide long-term sub-hourly records of cloud top temperatures, raising the possibility of combining these with the high-quality rainfall data from TRMM. In this study, we relate TRMM 2A25 rainfall to Meteosat Second Generation (MSG) cloud top temperatures, which are available from 2004 at 15 minutes intervals, to get a more detailed picture of the structure of intense rainfall within the life cycle of MCS. We find TRMM rainfall intensities within an MCS to be strongly coupled with MSG cloud top temperatures: the probability for extreme rainfall increases from <10% for minimum temperatures warmer than -40°C to over 70% when temperatures drop below -70°C, confirming the potential in analysing cloud-top temperatures as a proxy for extreme rain. The sheer size of MCS raises the question which scales of sub-cloud structures are more likely to be associated with extreme rain than others. In the end, this information could help to associate scale changes in cloud top temperatures with processes that affect the probability of extreme rain. We use 2D continuous wavelets to decompose cloud top temperatures into power spectra at scales between 15 and 200km. From these, cloud sub-structures are identified as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-cloud features of different scales. We find a higher probability for extreme rainfall for cloud features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller cloud features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed cloud type. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-cloud structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.

Point Cloud Based Relative Pose Estimation of a Satellite in Close Range

PubMed Central

Liu, Lujiang; Zhao, Gaopeng; Bo, Yuming

2016-01-01

Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective. PMID:27271633

Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation

NASA Astrophysics Data System (ADS)

Budge, Scott E.; Badamikar, Neeraj S.; Xie, Xuan

2015-03-01

Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.

Comparison of the filtering models for airborne LiDAR data by three classifiers with exploration on model transfer

NASA Astrophysics Data System (ADS)

Ma, Hongchao; Cai, Zhan; Zhang, Liang

2018-01-01

This paper discusses airborne light detection and ranging (LiDAR) point cloud filtering (a binary classification problem) from the machine learning point of view. We compared three supervised classifiers for point cloud filtering, namely, Adaptive Boosting, support vector machine, and random forest (RF). Nineteen features were generated from raw LiDAR point cloud based on height and other geometric information within a given neighborhood. The test datasets issued by the International Society for Photogrammetry and Remote Sensing (ISPRS) were used to evaluate the performance of the three filtering algorithms; RF showed the best results with an average total error of 5.50%. The paper also makes tentative exploration in the application of transfer learning theory to point cloud filtering, which has not been introduced into the LiDAR field to the authors' knowledge. We performed filtering of three datasets from real projects carried out in China with RF models constructed by learning from the 15 ISPRS datasets and then transferred with little to no change of the parameters. Reliable results were achieved, especially in rural area (overall accuracy achieved 95.64%), indicating the feasibility of model transfer in the context of point cloud filtering for both easy automation and acceptable accuracy.

Coarse Point Cloud Registration by Egi Matching of Voxel Clusters

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Shen, Yueqian; Menenti, Massimo

2016-06-01

Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted in two steps, i.e. coarse registration followed by fine registration. In this study an automatic marker-free coarse registration method for pair-wise scans is presented. First the two input point clouds are re-sampled as voxels and dimensionality features of the voxels are determined by principal component analysis (PCA). Then voxel cells with the same dimensionality are clustered. Next, the Extended Gaussian Image (EGI) descriptor of those voxel clusters are constructed using significant eigenvectors of each voxel in the cluster. Correspondences between clusters in source and target data are obtained according to the similarity between their EGI descriptors. The random sampling consensus (RANSAC) algorithm is employed to remove outlying correspondences until a coarse alignment is obtained. If necessary, a fine registration is performed in a final step. This new method is illustrated on scan data sampling two indoor scenarios. The results of the tests are evaluated by computing the point to point distance between the two input point clouds. The presented two tests resulted in mean distances of 7.6 mm and 9.5 mm respectively, which are adequate for fine registration.

New Perspectives of Point Clouds Color Management - the Development of Tool in Matlab for Applications in Cultural Heritage

NASA Astrophysics Data System (ADS)

Pepe, M.; Ackermann, S.; Fregonese, L.; Achille, C.

2017-02-01

The paper describes a method for Point Clouds Color management and Integration obtained from Terrestrial Laser Scanner (TLS) and Image Based (IB) survey techniques. Especially in the Cultural Heritage (CH) environment, methods and techniques to improve the color quality of Point Clouds have a key role because a homogenous texture brings to a more accurate reconstruction of the investigated object and to a more pleasant perception of the color object as well. A color management method for point clouds can be useful in case of single data set acquired by TLS or IB technique as well as in case of chromatic heterogeneity resulting by merging different datasets. The latter condition can occur when the scans are acquired in different moments of the same day or when scans of the same object are performed in a period of weeks or months, and consequently with a different environment/lighting condition. In this paper, a procedure to balance the point cloud color in order to uniform the different data sets, to improve the chromatic quality and to highlight further details will be presented and discussed.

An improvement of the retrieval of temperature and relative humidity profiles from a combination of active and passive remote sensing

NASA Astrophysics Data System (ADS)

Che, Yunfei; Ma, Shuqing; Xing, Fenghua; Li, Siteng; Dai, Yaru

2018-03-01

This paper focuses on an improvement of the retrieval of atmospheric temperature and relative humidity profiles through combining active and passive remote sensing. Ground-based microwave radiometer and millimeter-wavelength cloud radar were used to acquire the observations. Cloud base height and cloud thickness determinations from cloud radar were added into the atmospheric profile retrieval process, and a back-propagation neural network method was used as the retrieval tool. Because a substantial amount of data are required to train a neural network, and as microwave radiometer data are insufficient for this purpose, 8 years of radiosonde data from Beijing were used as the database. The monochromatic radiative transfer model was used to calculate the brightness temperatures in the same channels as the microwave radiometer. Parts of the cloud base heights and cloud thicknesses in the training data set were also estimated using the radiosonde data. The accuracy of the results was analyzed through a comparison with L-band sounding radar data and quantified using the mean bias, root-mean-square error (RMSE), and correlation coefficient. The statistical results showed that an inversion with cloud information was the optimal method. Compared with the inversion profiles without cloud information, the RMSE values after adding cloud information reduced to varying degrees for the vast majority of height layers. These reductions were particularly clear in layers with clouds. The maximum reduction in the RMSE for the temperature profile was 2.2 K, while that for the humidity profile was 16%.

Cirrus clouds as seen by the CALIPSO satellite and ECHAM-HAM global climate model

NASA Astrophysics Data System (ADS)

Gasparini, Blaz; Meyer, Angela; Neubauer, David; Münch, Steffen; Lohmann, Ulrike

2017-04-01

Ice clouds impact the planetary energy balance and upper tropospheric water vapour transport and are therefore relevant for climate. In this study ice clouds at temperatures below -40°C simulated by the ECHAM-HAM global climate model are compared to CALIPSO/CALIOP satellite data. The model reproduces well the mean occurrence of ice clouds, while the ice water path, ice crystal radius, cloud optical depth and extinction are overestimated in terms of annual means and temperature dependent frequency histograms. Two distinct types of cirrus clouds are found: in-situ formed cirrus dominating at temperatures below -60°C and liquid-origin cirrus, dominating at temperatures warmer than -55°C. The latter form in anvils of deep convective clouds or by glaciation of mixed-phase clouds. They are associated with ice water contents of up to 0.1 g m-3 and extinctions of up to 0.1 km-1, while the in-situ formed cirrus are optically thinner and contain at least an order of magnitude less ice. The ice cloud properties do not differ significantly between the southern and the northern hemisphere. In-situ formed ice clouds are further divided into homogeneously and heterogeneously nucleated ones. The simulated liquid-origin ice crystals mainly form in convective outflow in large number concentrations, similar to in-situ homogeneously nucleated ice crystals. On the contrary, heterogeneously nucleated ice crystals are associated with smaller number concentrations. However, ice crystal aggregation and depositional growth smooth the differences between several formation mechanisms making the attribution to a specific ice nucleation mechanism challenging.

Transitions in the Cloud Composition of Hot Jupiters

NASA Astrophysics Data System (ADS)

Parmentier, Vivien; Fortney, Jonathan J.; Showman, Adam P.; Morley, Caroline; Marley, Mark S.

2016-09-01

Over a large range of equilibrium temperatures, clouds shape the transmission spectrum of hot Jupiter atmospheres, yet their composition remains unknown. Recent observations show that the Kepler light curves of some hot Jupiters are asymmetric: for the hottest planets, the light curve peaks before secondary eclipse, whereas for planets cooler than ˜1900 K, it peaks after secondary eclipse. We use the thermal structure from 3D global circulation models to determine the expected cloud distribution and Kepler light curves of hot Jupiters. We demonstrate that the change from an optical light curve dominated by thermal emission to one dominated by scattering (reflection) naturally explains the observed trend from negative to positive offset. For the cool planets the presence of an asymmetry in the Kepler light curve is a telltale sign of the cloud composition, because each cloud species can produce an offset only over a narrow range of effective temperatures. By comparing our models and the observations, we show that the cloud composition of hot Jupiters likely varies with equilibrium temperature. We suggest that a transition occurs between silicate and manganese sulfide clouds at a temperature near 1600 K, analogous to the L/T transition on brown dwarfs. The cold trapping of cloud species below the photosphere naturally produces such a transition and predicts similar transitions for other condensates, including TiO. We predict that most hot Jupiters should have cloudy nightsides, that partial cloudiness should be common at the limb, and that the dayside hot spot should often be cloud-free.

Classification of Aerial Photogrammetric 3d Point Clouds

NASA Astrophysics Data System (ADS)

Becker, C.; Häni, N.; Rosinskaya, E.; d'Angelo, E.; Strecha, C.

2017-05-01

We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer.

Ice Cloud Formation and Dehydration in the Tropical Tropopause Layer

NASA Technical Reports Server (NTRS)

Jensen, Eric; Gore, Warren J. (Technical Monitor)

2002-01-01

Stratospheric water vapor is important not only for its greenhouse forcing, but also because it plays a significant role in stratospheric chemistry. Several recent studies have focused on the potential for dehydration due to ice cloud formation in air rising slowly through the tropical tropopause layer (TTL). Holton and Gettelman showed that temperature variations associated with horizontal transport of air in the TTL can drive ice cloud formation and dehydration, and Gettelman et al. recently examined the cloud formation and dehydration along kinematic trajectories using simple assumptions about the cloud properties. In this study, a Lagrangian, one-dimensional cloud model has been used to further investigate cloud formation and dehydration as air is transported horizontally and vertically through the TTL. Time-height curtains of temperature are extracted from meteorological analyses. The model tracks the growth, advection, and sedimentation of individual cloud particles. The regional distribution of clouds simulated in the model is comparable to the subvisible cirrus distribution indicated by SAGE II. The simulated cloud properties and cloud frequencies depend strongly on the assumed supersaturation threshold for ice nucleation. The clouds typically do not dehydrate the air along trajectories down to the temperature minimum saturation mixing ratio. Rather the water vapor mixing ratio crossing the tropopause along trajectories is 10-50% larger than the saturation mixing ratio. I will also discuss the impacts of Kelvin waves and gravity waves on cloud properties and dehydration efficiency. These simulations can be used to determine whether observed lower stratospheric water vapor mixing ratios can be explained by dehydration associated with in situ TTL cloud formation alone.

Infrared remote sensing of the vertical and horizontal distribution of clouds

NASA Technical Reports Server (NTRS)

Chahine, M. T.; Haskins, R. D.

1982-01-01

An algorithm has been developed to derive the horizontal and vertical distribution of clouds from the same set of infrared radiance data used to retrieve atmospheric temperature profiles. The method leads to the determination of the vertical atmospheric temperature structure and the cloud distribution simultaneously, providing information on heat sources and sinks, storage rates and transport phenomena in the atmosphere. Experimental verification of this algorithm was obtained using the 15-micron data measured by the NOAA-VTPR temperature sounder. After correcting for water vapor emission, the results show that the cloud cover derived from 15-micron data is less than that obtained from visible data.

The 1980 stratospheric-tropospheric exchange experiment

NASA Technical Reports Server (NTRS)

Margozzi, A. P. (Editor)

1983-01-01

Data are presented from the Stratospheric-Tropospheric Water Vapor Exchange Experiment. Measurements were made during 11 flights of the NASA U-2 aircraft which provided data from horizontal traverser and samplings in and about the tops of extensive cirrus-anvil clouds produced by overshooting cumulus turrets. Aircraft measurements were made of water vapor, ozone, ambient and cloud top temperature, fluorocarbons, nitrous oxide, nitric acid, aerosols, and ice crystal populations. Balloonsondes were flown about twice daily providing data on ozone, wind fields, pressure and temperature to altitudes near 30 km. Satellite photography provided detailed cloud and cloud top temperature information. Descriptions of individual experiments and detailed compilations of all results are provided.

Application of mixed cloud point extraction for the analysis of six flavonoids in Apocynum venetum leaf samples by high performance liquid chromatography.

PubMed

Zhou, Jun; Sun, Jiang Bing; Xu, Xin Yu; Cheng, Zhao Hui; Zeng, Ping; Wang, Feng Qiao; Zhang, Qiong

2015-03-25

A simple, inexpensive and efficient method based on the mixed cloud point extraction (MCPE) combined with high performance liquid chromatography was developed for the simultaneous separation and determination of six flavonoids (rutin, hyperoside, quercetin-3-O-sophoroside, isoquercitrin, astragalin and quercetin) in Apocynum venetum leaf samples. The non-ionic surfactant Genapol X-080 and cetyl-trimethyl ammonium bromide (CTAB) was chosen as the mixed extracting solvent. Parameters that affect the MCPE processes, such as the content of Genapol X-080 and CTAB, pH, salt content, extraction temperature and time were investigated and optimized. Under the optimized conditions, the calibration curve for six flavonoids were all linear with the correlation coefficients greater than 0.9994. The intra-day and inter-day precision (RSD) were below 8.1% and the limits of detection (LOD) for the six flavonoids were 1.2-5.0 ng mL(-1) (S/N=3). The proposed method was successfully used to separate and determine the six flavonoids in A. venetum leaf samples. Copyright © 2015 Elsevier B.V. All rights reserved.

A simple method for determination of carmine in food samples based on cloud point extraction and spectrophotometric detection.

PubMed

Heydari, Rouhollah; Hosseini, Mohammad; Zarabi, Sanaz

2015-01-01

In this paper, a simple and cost effective method was developed for extraction and pre-concentration of carmine in food samples by using cloud point extraction (CPE) prior to its spectrophotometric determination. Carmine was extracted from aqueous solution using Triton X-100 as extracting solvent. The effects of main parameters such as solution pH, surfactant and salt concentrations, incubation time and temperature were investigated and optimized. Calibration graph was linear in the range of 0.04-5.0 μg mL(-1) of carmine in the initial solution with regression coefficient of 0.9995. The limit of detection (LOD) and limit of quantification were 0.012 and 0.04 μg mL(-1), respectively. Relative standard deviation (RSD) at low concentration level (0.05 μg mL(-1)) of carmine was 4.8% (n=7). Recovery values in different concentration levels were in the range of 93.7-105.8%. The obtained results demonstrate the proposed method can be applied satisfactory to determine the carmine in food samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Microphysical Processes Affecting the Pinatubo Volcanic Plume

NASA Technical Reports Server (NTRS)

Hamill, Patrick; Houben, Howard; Young, Richard; Turco, Richard; Zhao, Jingxia

1996-01-01

In this paper we consider microphysical processes which affect the formation of sulfate particles and their size distribution in a dispersing cloud. A model for the dispersion of the Mt. Pinatubo volcanic cloud is described. We then consider a single point in the dispersing cloud and study the effects of nucleation, condensation and coagulation on the time evolution of the particle size distribution at that point.

Low clouds suppress Arctic air formation and amplify high-latitude continental winter warming.

PubMed

Cronin, Timothy W; Tziperman, Eli

2015-09-15

High-latitude continents have warmed much more rapidly in recent decades than the rest of the globe, especially in winter, and the maintenance of warm, frost-free conditions in continental interiors in winter has been a long-standing problem of past equable climates. We use an idealized single-column atmospheric model across a range of conditions to study the polar night process of air mass transformation from high-latitude maritime air, with a prescribed initial temperature profile, to much colder high-latitude continental air. We find that a low-cloud feedback--consisting of a robust increase in the duration of optically thick liquid clouds with warming of the initial state--slows radiative cooling of the surface and amplifies continental warming. This low-cloud feedback increases the continental surface air temperature by roughly two degrees for each degree increase of the initial maritime surface air temperature, effectively suppressing Arctic air formation. The time it takes for the surface air temperature to drop below freezing increases nonlinearly to ∼ 10 d for initial maritime surface air temperatures of 20 °C. These results, supplemented by an analysis of Coupled Model Intercomparison Project phase 5 climate model runs that shows large increases in cloud water path and surface cloud longwave forcing in warmer climates, suggest that the "lapse rate feedback" in simulations of anthropogenic climate change may be related to the influence of low clouds on the stratification of the lower troposphere. The results also indicate that optically thick stratus cloud decks could help to maintain frost-free winter continental interiors in equable climates.

Low clouds suppress Arctic air formation and amplify high-latitude continental winter warming

PubMed Central

Cronin, Timothy W.; Tziperman, Eli

2015-01-01

High-latitude continents have warmed much more rapidly in recent decades than the rest of the globe, especially in winter, and the maintenance of warm, frost-free conditions in continental interiors in winter has been a long-standing problem of past equable climates. We use an idealized single-column atmospheric model across a range of conditions to study the polar night process of air mass transformation from high-latitude maritime air, with a prescribed initial temperature profile, to much colder high-latitude continental air. We find that a low-cloud feedback—consisting of a robust increase in the duration of optically thick liquid clouds with warming of the initial state—slows radiative cooling of the surface and amplifies continental warming. This low-cloud feedback increases the continental surface air temperature by roughly two degrees for each degree increase of the initial maritime surface air temperature, effectively suppressing Arctic air formation. The time it takes for the surface air temperature to drop below freezing increases nonlinearly to ∼10 d for initial maritime surface air temperatures of 20 °C. These results, supplemented by an analysis of Coupled Model Intercomparison Project phase 5 climate model runs that shows large increases in cloud water path and surface cloud longwave forcing in warmer climates, suggest that the “lapse rate feedback” in simulations of anthropogenic climate change may be related to the influence of low clouds on the stratification of the lower troposphere. The results also indicate that optically thick stratus cloud decks could help to maintain frost-free winter continental interiors in equable climates. PMID:26324919

3D local feature BKD to extract road information from mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

2017-08-01

Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images

NASA Astrophysics Data System (ADS)

Xie, L.; Hu, H.; Zhu, Q.; Wu, B.; Zhang, Y.

2017-05-01

Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

Noctilucent cloud formation and the effects of water vapor variability on temperatures in the middle atmosphere

NASA Technical Reports Server (NTRS)

Mckay, C. P.

1985-01-01

To investigate the occurrence of low temperatures and the formation of noctilucent clouds in the summer mesosphere, a one-dimensional time-dependent photochemical-thermal numerical model of the atmosphere between 50 and 120 km has been constructed. The model self-consistently solves the coupled photochemical and thermal equations as perturbation equations from a reference state assumed to be in equilibrium and is used to consider the effect of variability in water vapor in the lower mesosphere on the temperature in the region of noctilucent cloud formation. It is found that change in water vapor from an equilibrium value of 5 ppm at 50 km to a value of 10 ppm, a variation consistent with observations, can produce a roughly 15 K drop in temperature at 82 km. It is suggested that this process may produce weeks of cold temperatures and influence noctilucent cloud formation.

Multiview 3D sensing and analysis for high quality point cloud reconstruction

NASA Astrophysics Data System (ADS)

Satnik, Andrej; Izquierdo, Ebroul; Orjesek, Richard

2018-04-01

Multiview 3D reconstruction techniques enable digital reconstruction of 3D objects from the real world by fusing different viewpoints of the same object into a single 3D representation. This process is by no means trivial and the acquisition of high quality point cloud representations of dynamic 3D objects is still an open problem. In this paper, an approach for high fidelity 3D point cloud generation using low cost 3D sensing hardware is presented. The proposed approach runs in an efficient low-cost hardware setting based on several Kinect v2 scanners connected to a single PC. It performs autocalibration and runs in real-time exploiting an efficient composition of several filtering methods including Radius Outlier Removal (ROR), Weighted Median filter (WM) and Weighted Inter-Frame Average filtering (WIFA). The performance of the proposed method has been demonstrated through efficient acquisition of dense 3D point clouds of moving objects.

Performance testing of 3D point cloud software

NASA Astrophysics Data System (ADS)

Varela-González, M.; González-Jorge, H.; Riveiro, B.; Arias, P.

2013-10-01

LiDAR systems are being used widely in recent years for many applications in the engineering field: civil engineering, cultural heritage, mining, industry and environmental engineering. One of the most important limitations of this technology is the large computational requirements involved in data processing, especially for large mobile LiDAR datasets. Several software solutions for data managing are available in the market, including open source suites, however, users often unknown methodologies to verify their performance properly. In this work a methodology for LiDAR software performance testing is presented and four different suites are studied: QT Modeler, VR Mesh, AutoCAD 3D Civil and the Point Cloud Library running in software developed at the University of Vigo (SITEGI). The software based on the Point Cloud Library shows better results in the loading time of the point clouds and CPU usage. However, it is not as strong as commercial suites in working set and commit size tests.

Triangulation Error Analysis for the Barium Ion Cloud Experiment. M.S. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Long, S. A. T.

1973-01-01

The triangulation method developed specifically for the Barium Ion Cloud Project is discussed. Expression for the four displacement errors, the three slope errors, and the curvature error in the triangulation solution due to a probable error in the lines-of-sight from the observation stations to points on the cloud are derived. The triangulation method is then used to determine the effect of the following on these different errors in the solution: the number and location of the stations, the observation duration, east-west cloud drift, the number of input data points, and the addition of extra cameras to one of the stations. The pointing displacement errors, and the pointing slope errors are compared. The displacement errors in the solution due to a probable error in the position of a moving station plus the weighting factors for the data from the moving station are also determined.

3D reconstruction of wooden member of ancient architecture from point clouds

NASA Astrophysics Data System (ADS)

Zhang, Ruiju; Wang, Yanmin; Li, Deren; Zhao, Jun; Song, Daixue

2006-10-01

This paper presents a 3D reconstruction method to model wooden member of ancient architecture from point clouds based on improved deformable model. Three steps are taken to recover the shape of wooden member. Firstly, Hessian matrix is adopted to compute the axe of wooden member. Secondly, an initial model of wooden member is made by contour orthogonal to its axis. Thirdly, an accurate model is got through the coupling effect between the initial model and the point clouds of the wooden member according to the theory of improved deformable model. Every step and algorithm is studied and described in the paper. Using the point clouds captured from Forbidden City of China, shaft member and beam member are taken as examples to test the method proposed in the paper. Results show the efficiency and robustness of the method addressed in the literature to model the wooden member of ancient architecture.

On the Surface Formation of NH3 and HNCO in Dark Molecular Clouds - Searching for Wöhler Synthesis in the Interstellar Medium

NASA Astrophysics Data System (ADS)

Fedoseev, Gleb; Lamberts, Thanja; Linnartz, Harold; Ioppolo, Sergio; Zhao, Dongfeng

Despite its potential to reveal the link between the formation of simple species and more complex molecules (e.g., amino acids), the nitrogen chemistry of the interstellar medium (ISM) is still poorly understood. Ammonia (NH _{3}) is one of the few nitrogen-bearing species that have been observed in interstellar ices toward young stellar objects (YSOs) and quiescent molecular clouds. The aim of the present work is to experimentally investigate surface formation routes of NH _{3} and HNCO through non-energetic surface reactions in interstellar ice analogues under fully controlled laboratory conditions and at astrochemically relevant cryogenic temperatures. This study focuses on the formation of NH _{3} and HNCO in CO-rich (non-polar) interstellar ices that simulate the CO freeze-out stage in interstellar dark cloud regions, well before thermal and energetic processing start to become predominant. Our work confirms the surface formation of ammonia through the sequential addition of three hydrogen/deuterium atoms to a single nitrogen atom at low temperature. The H/D fractionation of the formed ammonia is also shown. Furthermore, we show the surface formation of solid HNCO through the interaction of CO molecules with NH radicals - one of the intermediates in the formation of solid NH _{3}. Finally, we discuss the implications of HNCO in astrobiology, as a possible starting point for the formation of more complex prebiotic species.

High Abundance of Ions in Cosmic Ices

NASA Technical Reports Server (NTRS)

Gudipati, Murthy S.; Allamandola, Louis J.; Fonda, Mark (Technical Monitor)

2002-01-01

Water-rich, mixed molecular ices and polycyclic aromatic hydrocarbons (PAHs) are common throughout interstellar molecular clouds and the Solar System. Vacuum ultraviolet (VUV) irradiation and particle bombardment of these abiotic ices produces complex organic species, including important biogenic molecules such as amino acids and functionalized PAHs which may have played a role in the origin of life. This ability of such water-rich, oxygen dominated ices to promote production of complex organic species is surprising and points to an important, unusual, but previously overlooked mechanism at play within the ice. Here we report the nature of this mechanism using electronic spectroscopy. VUV-irradiation of PAH/H2O ices leads to an unprecedented and efficient (greater than 70 %) conversion of the neutral PAHs to their cation form (PAH+). Further, these H2O/PAH+ ices are stabile at temperatures below 50 K, a temperature domain common throughout interstellar clouds and the Solar System. Between 50 and 125 K they react to form the complex organics. In view of this, we conclude that charged PAHs and other molecular ions should be common and abundant in many cosmic ices. The chemical, spectroscopic and physical properties of these ion-rich ices can be of fundamental importance for objects as diverse as comets, planets, and molecular clouds and may account for several poorly understood phenomena associated with each of these object classes.

Implementation of Cloud Retrievals for Tropospheric Emission Spectrometer (TES) Atmospheric Retrievals: Part 1. Description and Characterization of Errors on Trace Gas Retrievals

NASA Technical Reports Server (NTRS)

Kulawik, Susan S.; Worden, John; Eldering, Annmarie; Bowman, Kevin; Gunson, Michael; Osterman, Gregory B.; Zhang, Lin; Clough, Shepard A.; Shephard, Mark W.; Beer, Reinhard

2006-01-01

We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

Characterizing sampling and quality screening biases in infrared and microwave limb sounding

NASA Astrophysics Data System (ADS)

Millán, Luis F.; Livesey, Nathaniel J.; Santee, Michelle L.; von Clarmann, Thomas

2018-03-01

This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper-tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper-tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although its penetration is limited to the upper troposphere, while MIPAS may cover well into the mid-troposphere in cloud-free scenarios. We emphasize that the results of this study refer only to the representativeness of the respective data, not to their intrinsic quality.

Why is the Magellanic Stream so Turbulent? - A Simulational Study

NASA Astrophysics Data System (ADS)

Williams, Elliott; Shelton, Robin L.

2018-06-01

As the Large and Small Magellanic Clouds travel through the Milky Way (MW) halo, gas is tidally and ram pressure stripped from them, forming the Leading Arm (LA) and Magellanic Stream (MS). The evolution of the LA and MS are an interest to astronomers because there is evidence that the diffuse gas that has been stripped off is able to fall onto the galactic disk and cool enough to fuel star formation in the MW. For et al, 2014 published a catalog of 251 high velocity clouds (HVCs) in the MS, many of which have head-tail morphologies, suggesting interaction with the Milky Way’s halo or other gas in the MS. For et al noticed that the pointing direction of the HVCs are random, which they interpreted as an indication of strong turbulence. They suggested the shock cascade scenario as a contributing process, where ablated cloud material generates turbulence (and H-alpha emission). We take a closer look at this process via simulations. We ran numerical simulations of clouds in the MS using the University of Chicago’s FLASH software. We simulated cases that had two clouds, where one trailed behind the other, and we simulated cases that had one cloud in order to examine the effects of drafting on cloud dynamics and velocity dispersion. Initial cloud temperatures ranged from 100 K to 20,000 K. We have created velocity dispersion maps from the FLASH simulation data to visualize turbulence. We compare these generated maps with 21 cm observations (most recently Westmeier, 2017), in order to search for signatures similar to the small scale turbulence seen in the simulations. We find that if the clouds are initially near to each other, then drafting allows the trailing cloud to catch the leading cloud and mix together. For greater separations, Kelvin-Helmholtz instabilities disrupt the clouds enough before impact that drafting has a minimal role. Our velocity dispersion maps of the warmer clouds closely match values published in For et al, 2014; although, thermal broadening accounts for a large fraction of the velocity dispersion found in the generated maps.

Comparision of photogrammetric point clouds with BIM building elements for construction progress monitoring

NASA Astrophysics Data System (ADS)

Tuttas, S.; Braun, A.; Borrmann, A.; Stilla, U.

2014-08-01

For construction progress monitoring a planned state of the construction at a certain time (as-planed) has to be compared to the actual state (as-built). The as-planed state is derived from a building information model (BIM), which contains the geometry of the building and the construction schedule. In this paper we introduce an approach for the generation of an as-built point cloud by photogrammetry. It is regarded that that images on a construction cannot be taken from everywhere it seems to be necessary. Because of this we use a combination of structure from motion process together with control points to create a scaled point cloud in a consistent coordinate system. Subsequently this point cloud is used for an as-built - as-planed comparison. For that voxels of an octree are marked as occupied, free or unknown by raycasting based on the triangulated points and the camera positions. This allows to identify not existing building parts. For the verification of the existence of building parts a second test based on the points in front and behind the as-planed model planes is performed. The proposed procedure is tested based on an inner city construction site under real conditions.

Localization of Pathology on Complex Architecture Building Surfaces

NASA Astrophysics Data System (ADS)

Sidiropoulos, A. A.; Lakakis, K. N.; Mouza, V. K.

2017-02-01

The technology of 3D laser scanning is considered as one of the most common methods for heritage documentation. The point clouds that are being produced provide information of high detail, both geometric and thematic. There are various studies that examine techniques of the best exploitation of this information. In this study, an algorithm of pathology localization, such as cracks and fissures, on complex building surfaces is being tested. The algorithm makes use of the points' position in the point cloud and tries to distinguish them in two groups-patterns; pathology and non-pathology. The extraction of the geometric information that is being used for recognizing the pattern of the points is being accomplished via Principal Component Analysis (PCA) in user-specified neighborhoods in the whole point cloud. The implementation of PCA leads to the definition of the normal vector at each point of the cloud. Two tests that operate separately examine both local and global geometric criteria among the points and conclude which of them should be categorized as pathology. The proposed algorithm was tested on parts of the Gazi Evrenos Baths masonry, which are located at the city of Giannitsa at Northern Greece.

Error reduction in three-dimensional metrology combining optical and touch probe data

NASA Astrophysics Data System (ADS)

Gerde, Janice R.; Christens-Barry, William A.

2010-08-01

Analysis of footwear under the Harmonized Tariff Schedule of the United States (HTSUS) is partly based on identifying the boundary ("parting line") between the "external surface area upper" (ESAU) and the sample's sole. Often, that boundary is obscured. We establish the parting line as the curved intersection between the sample outer surface and its insole surface. The outer surface is determined by discrete point cloud coordinates obtained using a laser scanner. The insole surface is defined by point cloud data, obtained using a touch probe device-a coordinate measuring machine (CMM). Because these point cloud data sets do not overlap spatially, a polynomial surface is fitted to the insole data and extended to intersect a mesh fitted to the outer surface point cloud. This line of intersection defines the ESAU boundary, permitting further fractional area calculations to proceed. The defined parting line location is sensitive to the polynomial used to fit experimental data. Extrapolation to the intersection with the ESAU can heighten this sensitivity. We discuss a methodology for transforming these data into a common reference frame. Three scenarios are considered: measurement error in point cloud coordinates, from fitting a polynomial surface to a point cloud then extrapolating beyond the data set, and error from reference frame transformation. These error sources can influence calculated surface areas. We describe experiments to assess error magnitude, the sensitivity of calculated results on these errors, and minimizing error impact on calculated quantities. Ultimately, we must ensure that statistical error from these procedures is minimized and within acceptance criteria.

Photogrammetric DSM denoising

NASA Astrophysics Data System (ADS)

Nex, F.; Gerke, M.

2014-08-01

Image matching techniques can nowadays provide very dense point clouds and they are often considered a valid alternative to LiDAR point cloud. However, photogrammetric point clouds are often characterized by a higher level of random noise compared to LiDAR data and by the presence of large outliers. These problems constitute a limitation in the practical use of photogrammetric data for many applications but an effective way to enhance the generated point cloud has still to be found. In this paper we concentrate on the restoration of Digital Surface Models (DSM), computed from dense image matching point clouds. A photogrammetric DSM, i.e. a 2.5D representation of the surface is still one of the major products derived from point clouds. Four different algorithms devoted to DSM denoising are presented: a standard median filter approach, a bilateral filter, a variational approach (TGV: Total Generalized Variation), as well as a newly developed algorithm, which is embedded into a Markov Random Field (MRF) framework and optimized through graph-cuts. The ability of each algorithm to recover the original DSM has been quantitatively evaluated. To do that, a synthetic DSM has been generated and different typologies of noise have been added to mimic the typical errors of photogrammetric DSMs. The evaluation reveals that standard filters like median and edge preserving smoothing through a bilateral filter approach cannot sufficiently remove typical errors occurring in a photogrammetric DSM. The TGV-based approach much better removes random noise, but large areas with outliers still remain. Our own method which explicitly models the degradation properties of those DSM outperforms the others in all aspects.

Scan-To Output Validation: Towards a Standardized Geometric Quality Assessment of Building Information Models Based on Point Clouds

NASA Astrophysics Data System (ADS)

Bonduel, M.; Bassier, M.; Vergauwen, M.; Pauwels, P.; Klein, R.

2017-11-01

The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Utilizing the Iterative Closest Point (ICP) algorithm for enhanced registration of high resolution surface models - more than a simple black-box application

NASA Astrophysics Data System (ADS)

Stöcker, Claudia; Eltner, Anette

2016-04-01

Advances in computer vision and digital photogrammetry (i.e. structure from motion) allow for fast and flexible high resolution data supply. Within geoscience applications and especially in the field of small surface topography, high resolution digital terrain models and dense 3D point clouds are valuable data sources to capture actual states as well as for multi-temporal studies. However, there are still some limitations regarding robust registration and accuracy demands (e.g. systematic positional errors) which impede the comparison and/or combination of multi-sensor data products. Therefore, post-processing of 3D point clouds can heavily enhance data quality. In this matter the Iterative Closest Point (ICP) algorithm represents an alignment tool which iteratively minimizes distances of corresponding points within two datasets. Even though tool is widely used; it is often applied as a black-box application within 3D data post-processing for surface reconstruction. Aiming for precise and accurate combination of multi-sensor data sets, this study looks closely at different variants of the ICP algorithm including sub-steps of point selection, point matching, weighting, rejection, error metric and minimization. Therefore, an agricultural utilized field was investigated simultaneously by terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) sensors two times (once covered with sparse vegetation and once bare soil). Due to different perspectives both data sets show diverse consistency in terms of shadowed areas and thus gaps so that data merging would provide consistent surface reconstruction. Although photogrammetric processing already included sub-cm accurate ground control surveys, UAV point cloud exhibits an offset towards TLS point cloud. In order to achieve the transformation matrix for fine registration of UAV point clouds, different ICP variants were tested. Statistical analyses of the results show that final success of registration and therefore data quality depends particularly on parameterization and choice of error metric, especially for erroneous data sets as in the case of sparse vegetation cover. At this, the point-to-point metric is more sensitive to data "noise" than the point-to-plane metric which results in considerably higher cloud-to-cloud distances. Concluding, in order to comply with accuracy demands of high resolution surface reconstruction and the aspect that ground control surveys can reach their limits both in time exposure and terrain accessibility ICP algorithm represents a great tool to refine rough initial alignment. Here different variants of registration modules allow for individual application according to the quality of the input data.

Ice particle morphology and microphysical properties of cirrus clouds inferred from combined CALIOP-IIR measurements

NASA Astrophysics Data System (ADS)

Saito, Masanori; Iwabuchi, Hironobu; Yang, Ping; Tang, Guanglin; King, Michael D.; Sekiguchi, Miho

2017-04-01

Ice particle morphology and microphysical properties of cirrus clouds are essential for assessing radiative forcing associated with these clouds. We develop an optimal estimation-based algorithm to infer cirrus cloud optical thickness (COT), cloud effective radius (CER), plate fraction including quasi-horizontally oriented plates (HOPs), and the degree of surface roughness from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Infrared Imaging Radiometer (IIR) on the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) platform. A simple but realistic ice particle model is used, and the relevant bulk optical properties are computed using state-of-the-art light-scattering computational capabilities. Rigorous estimation of uncertainties related to surface properties, atmospheric gases, and cloud heterogeneity is performed. The results based on the present method show that COTs are quite consistent with other satellite products and CERs essentially agree with the other counterparts. A 1 month global analysis for April 2007, in which CALIPSO off-nadir angle is 0.3°, shows that the HOP has significant temperature-dependence and is critical to the lidar ratio when cloud temperature is warmer than -40°C. The lidar ratio is calculated from the bulk optical properties based on the inferred parameters, showing robust temperature dependence. The median lidar ratio of cirrus clouds is 27-31 sr over the globe.

Chance Encounter with a Stratospheric Kerosene Rocket Plume From Russia Over California

NASA Technical Reports Server (NTRS)

Newman, P. A.; Wilson, J. C.; Ross, M. N.; Brock, C. A.; Sheridan, P. J.; Schoeberl, M. R.; Lait, L. R.; Bui, T. P.; Loewenstein, M.; Podolske, J. R.;

TEMPERATURE DISTRIBUTION IN A DIFFUSION CLOUD CHAMBER

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

Slavic, I.; Szymakowski, J.; Stachorska, D.

1961-03-01

A diffusion cloud chamber with working conditions within a pressure range from 10 mm Hg to 2 atmospheres and at variable boundary surface temperatures in a wide interval is described. A simple procedure is described for cooling and thermoregulating the bottom of the chamber by means of vapor flow of liquid air which makes possible the achievement of temperature up to -120 deg C with stability better that plus or minus 1 deg C. A method for the measurement of temperature distribution by means of a thermistor is described, and a number of curves of the observed temperature gradient, dependentmore » on the boundary surface temperature is given. Analysis of other factors influencing the stable work of the diffusion cloud chamber was made. (auth)« less

Warm gas towards young stellar objects in Corona Australis. Herschel/PACS observations from the DIGIT key programme

NASA Astrophysics Data System (ADS)

Lindberg, Johan E.; Jørgensen, Jes K.; Green, Joel D.; Herczeg, Gregory J.; Dionatos, Odysseas; Evans, Neal J.; Karska, Agata; Wampfler, Susanne F.

2014-05-01

Context. The effects of external irradiation on the chemistry and physics in the protostellar envelope around low-mass young stellar objects are poorly understood. The Corona Australis star-forming region contains the R CrA dark cloud, comprising several low-mass protostellar cores irradiated by an intermediate-mass young star. Aims: We study the effects of the irradiation coming from the young luminous Herbig Be star R CrA on the warm gas and dust in a group of low-mass young stellar objects. Methods: Herschel/PACS far-infrared datacubes of two low-mass star-forming regions in the R CrA dark cloud are presented. The distributions of CO, OH, H2O, [C ii], [O i], and continuum emission are investigated. We have developed a deconvolution algorithm which we use to deconvolve the maps, separating the point-source emission from the extended emission. We also construct rotational diagrams of the molecular species. Results: By deconvolution of the Herschel data, we find large-scale (several thousand AU) dust continuum and spectral line emission not associated with the point sources. Similar rotational temperatures are found for the warm CO (282 ± 4 K), hot CO (890 ± 84 K), OH (79 ± 4 K), and H2O (197 ± 7 K) emission in the point sources and the extended emission. The rotational temperatures are also similar to those found in other more isolated cores. The extended dust continuum emission is found in two ridges similar in extent and temperature to molecular millimetre emission, indicative of external heating from the Herbig Be star R CrA. Conclusions: Our results show that nearby luminous stars do not increase the molecular excitation temperatures of the warm gas around young stellar objects (YSOs). However, the emission from photodissociation products of H2O, such as OH and O, is enhanced in the warm gas associated with these protostars and their surroundings compared to similar objects not subjected to external irradiation. Table 9 and appendices are available in electronic form at http://www.aanda.org

First experimental evidence for carbon starvation at warm temperatures in epiphytic orchids of tropical cloud forests

NASA Astrophysics Data System (ADS)

Hoch, Guenter; Roemer, Helena; Fioroni, Tiffany; Olmedo, Inayat; Kahmen, Ansgar

2017-04-01

Tropical cloud forests are among the most climate sensitive ecosystems world-wide. The lack of a strong seasonality and the additional dampening of temperature fluctuations by the omnipresence of clouds and fog produce year-round constant climatic conditions. With climate change the presence of clouds and fog is, however, predicted to be reduced. The disappearance of the cooling fog cover will have dramatic consequences for air temperatures, that are predicted to increase locally well over 5 °C by the end of the 21st century. Especially the large number of endemic epiphytic orchids in tropical cloud forests that contribute substantially to the biological diversity of these ecosystems, but are typically adapted to a very narrow climate envelope, are speculated to be very sensitive to the anticipated rise in temperature. In a phytotron experiment we investigated the effect of increasing temperatures on the carbon balance (gas-exchange and the carbon reserve household) of 10 epiphytic orchid species from the genera Dracula, native to tropical, South-American cloud forests. The orchids were exposed to three temperature treatments: i) a constant temperature treatment (23°C/13°C, day/night) simulating natural conditions, ii) a slow temperature ramp of +0.75 K every 10 days, and iii) a fast temperature ramp of +1.5 K every 10 days. CO2 leaf gas-exchanges was determined every 10 days, and concentrations of low molecular weight sugars and starch were analyses from leaf samples throughout the experiment. We found that increasing temperatures had only minor effects on day-time leaf respiration, but led to a moderate increase of respiration during night-time. In contrast to the rather minor effects of higher temperatures on respiration, there was a dramatic decline of net-photosynthesis above day-time temperatures of 29°C, and a complete stop of net-carbon uptake at 33°C in all investigated species. This high sensitivity of photosynthesis to warming was independent of the speed of the temperature increase. Most importantly, the decline of photosynthesis was accompanied by a rapid and complete depletion of leaf starch reserves followed by the prompt death of the plants. We therefore conclude, that temperature increases to 29 - 33°C lead to carbon starvation in epiphytic orchids of tropical cloud forests that is driven by the break-down of photosynthesis. The physiological reason for the observed dysfunction of photosynthesis at only moderately warm temperatures are currently not well understood. Within an ongoing phytotron study, we thus are aiming to confirm and deepen the findings in the genus Dracula in Masdevallia, another orchid genera native and endemic to tropical cloud forests.

a Method for the Registration of Hemispherical Photographs and Tls Intensity Images

NASA Astrophysics Data System (ADS)

Schmidt, A.; Schilling, A.; Maas, H.-G.

2012-07-01

Terrestrial laser scanners generate dense and accurate 3D point clouds with minimal effort, which represent the geometry of real objects, while image data contains texture information of object surfaces. Based on the complementary characteristics of both data sets, a combination is very appealing for many applications, including forest-related tasks. In the scope of our research project, independent data sets of a plain birch stand have been taken by a full-spherical laser scanner and a hemispherical digital camera. Previously, both kinds of data sets have been considered separately: Individual trees were successfully extracted from large 3D point clouds, and so-called forest inventory parameters could be determined. Additionally, a simplified tree topology representation was retrieved. From hemispherical images, leaf area index (LAI) values, as a very relevant parameter for describing a stand, have been computed. The objective of our approach is to merge a 3D point cloud with image data in a way that RGB values are assigned to each 3D point. So far, segmentation and classification of TLS point clouds in forestry applications was mainly based on geometrical aspects of the data set. However, a 3D point cloud with colour information provides valuable cues exceeding simple statistical evaluation of geometrical object features and thus may facilitate the analysis of the scan data significantly.

Segmentation of Large Unstructured Point Clouds Using Octree-Based Region Growing and Conditional Random Fields

NASA Astrophysics Data System (ADS)

Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.

2017-11-01

Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.

An energy balance climate model with cloud feedbacks

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.

1984-01-01

The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small.

TRANSITIONS IN THE CLOUD COMPOSITION OF HOT JUPITERS

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

Parmentier, Vivien; Fortney, Jonathan J.; Morley, Caroline

Over a large range of equilibrium temperatures, clouds shape the transmission spectrum of hot Jupiter atmospheres, yet their composition remains unknown. Recent observations show that the Kepler light curves of some hot Jupiters are asymmetric: for the hottest planets, the light curve peaks before secondary eclipse, whereas for planets cooler than ∼1900 K, it peaks after secondary eclipse. We use the thermal structure from 3D global circulation models to determine the expected cloud distribution and Kepler light curves of hot Jupiters. We demonstrate that the change from an optical light curve dominated by thermal emission to one dominated by scatteringmore » (reflection) naturally explains the observed trend from negative to positive offset. For the cool planets the presence of an asymmetry in the Kepler light curve is a telltale sign of the cloud composition, because each cloud species can produce an offset only over a narrow range of effective temperatures. By comparing our models and the observations, we show that the cloud composition of hot Jupiters likely varies with equilibrium temperature. We suggest that a transition occurs between silicate and manganese sulfide clouds at a temperature near 1600 K, analogous to the L / T transition on brown dwarfs. The cold trapping of cloud species below the photosphere naturally produces such a transition and predicts similar transitions for other condensates, including TiO. We predict that most hot Jupiters should have cloudy nightsides, that partial cloudiness should be common at the limb, and that the dayside hot spot should often be cloud-free.« less

SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo

2017-06-01

Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate that the proposed method is able to recognize street furniture in a practical scenario. Remaining difficult cases are touching objects, like a lamp pole close to a tree.

Genomic cloud computing: legal and ethical points to consider

PubMed Central

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Burton, Paul; Chisholm, Rex; Fortier, Isabel; Goodwin, Pat; Harris, Jennifer; Hveem, Kristian; Kaye, Jane; Kent, Alistair; Knoppers, Bartha Maria; Lindpaintner, Klaus; Little, Julian; Riegman, Peter; Ripatti, Samuli; Stolk, Ronald; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn; Joly, Yann; Kato, Kazuto; Knoppers, Bartha Maria; Rodriguez, Laura Lyman; McPherson, Treasa; Nicolás, Pilar; Ouellette, Francis; Romeo-Casabona, Carlos; Sarin, Rajiv; Wallace, Susan; Wiesner, Georgia; Wilson, Julia; Zeps, Nikolajs; Simkevitz, Howard; De Rienzo, Assunta; Knoppers, Bartha M

2015-01-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key ‘points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These ‘points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure. PMID:25248396

Genomic cloud computing: legal and ethical points to consider.

PubMed

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Knoppers, Bartha M

2015-10-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

Sensitivity analysis of upwelling thermal radiance in presence of clouds

NASA Technical Reports Server (NTRS)

Subramanian, S. V.; Tiwari, S. N.; Suttles, J. T.

1981-01-01

Total upwelling radiance at the top of the atmosphere is evaluated theoretically in the presence of clouds. The influence of cloud heights, thicknesses and different cloud covers on the upwelling radiance is also investigated. The characteristics of the two cloud types considered in this study closely correspond to altocumulus and cirrus with the cloud emissivity as a function of its liquid water (or ice) content. For calculation of the integrated transmittance of atmospheric gases such as, H2O, CO2, O3, and N2O, the Quasi Random Band (QRB) model approach is adopted. Results are obtained in three different spectral ranges and are compared with the clearsky radiance results. It is found that the difference between the clearsky and cloudy radiance increases with increasing cloud height and liquid water content. This difference also decreases as the surface temperature approaches the value of the cloud top temperature.

Feedback mechanisms of shallow convective clouds in a warmer climate as demonstrated by changes in buoyancy

NASA Astrophysics Data System (ADS)

Dagan, G.; Koren, I.; Altaratz, O.; Feingold, G.

2018-05-01

Cloud feedbacks could influence significantly the overall response of the climate system to global warming. Here we study the response of warm convective clouds to a uniform temperature change under constant relative humidity (RH) conditions. We show that an increase in temperature drives competing effects at the cloud scale: a reduction in the thermal buoyancy term and an increase in the humidity buoyancy term. Both effects are driven by the increased contrast in the water vapor content between the cloud and its environment, under warming with constant RH. The increase in the moisture content contrast between the cloud and its environment enhances the evaporation at the cloud margins, increases the entrainment, and acts to cool the cloud. Hence, there is a reduction in the thermal buoyancy term, despite the fact that theoretically this term should increase.

Analysis of Meteorological Data Obtained During Flight in a Supercooled Stratiform Cloud of High Liquid-Water Content

NASA Technical Reports Server (NTRS)

Perkins, Porter J.; Kline, Dwight B.

1951-01-01

Flight icing-rate data obtained in a dense and. abnormally deep supercooled stratiform cloud system indicated the existence of liquid-water contents generally exceeding values in amount and extent previously reported over the midwestern sections of the United States. Additional information obtained during descent through a part of the cloud system indicated liquid-water contents that significantly exceeded theoretical values, especially near the middle of the cloud layer.. The growth of cloud droplets to sizes that resulted in sedimentation from the upper portions of the cloud is considered to be a possible cause of the high water contents near the center of the cloud layer. Flight measurements of the vertical temperature distribution in the cloud layer indicated a rate of change of temperature with altitude exceeding that of the moist adiabatic lapse rate. This excessive rate of change is considered to have contributed to the severity of the condition.

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.;

Partitioning of ice nucleating particles: Which modes matter?

NASA Astrophysics Data System (ADS)

Hande, Luke; Hoose, Corinna

2017-04-01

Ice particles in clouds have a large impact on cloud lifetime, precipitation amount, and cloud radiative properties through the indirect aerosol effect. Thus, correctly modelling ice formation processes is important for simulations preformed on all spatial and temporal scales. Ice forms on aerosol particles through several different mechanisms, namely deposition nucleation, immersion freezing, and contact freezing. However there is conflicting evidence as to which mode dominates, and the relative importance of the three heterogeneous ice nucleation mechanisms, as well as homogeneous nucleation, remains an open question. The environmental conditions, and hence the cloud type, have a large impact on determining which nucleation mode dominates. In order to understand this, simulations were performed with the COSMO-LES model, utilising state of the art parameterisations to describe the different nucleation mechanisms for several semi-idealised cloud types commonly occurring over central Europe. The cloud types investigated include a semi-idealised, and an idealised convective cloud, an orographic cloud, and a stratiform cloud. Results show that immersion and contact freezing dominate at warmer temperatures, and under most conditions, deposition nucleation plays only a minor role. In clouds where sufficiently high levels of water vapour are present at colder temperatures, deposition nucleation can play a role, however in general homogeneous nucleation dominates at colder temperatures. Since contact nucleation depends on the environmental relative humidity, enhancements in this nucleation mode can be seen in areas of dry air entrainment. The results indicate that ice microphysical processes are somewhat sensitve to the environmental conditions and therefore the cloud type.

Humidity trends imply increased sensitivity to clouds in a warming Arctic

DOE PAGES

Cox, Christopher J.; Walden, Von P.; Rowe, Penny M.; ...

2015-12-10

Infrared radiative processes are implicated in Arctic warming and sea-ice decline. The infrared cloud radiative effect (CRE) at the surface is modulated by cloud properties; however, CRE also depends on humidity because clouds emit at wavelengths that are semi-transparent to greenhouse gases, most notably water vapour. Here we show how temperature and humidity control CRE through competing influences between the mid- and far-infrared. At constant relative humidity, CRE does not decrease with increasing temperature/absolute humidity as expected, but rather is found to be approximately constant for temperatures characteristic of the Arctic. This stability is disrupted if relative humidity varies. Ourmore » findings explain observed seasonal and regional variability in Arctic CRE of order 10Wm 2. With the physical properties of Arctic clouds held constant, we calculate recent increases in CRE of 1–5Wm 2 in autumn and winter, which are projected to reach 5–15Wm 2 by 2050, implying increased sensitivity of the surface to clouds.« less

Humidity trends imply increased sensitivity to clouds in a warming Arctic.

PubMed

Cox, Christopher J; Walden, Von P; Rowe, Penny M; Shupe, Matthew D

2015-12-10

Infrared radiative processes are implicated in Arctic warming and sea-ice decline. The infrared cloud radiative effect (CRE) at the surface is modulated by cloud properties; however, CRE also depends on humidity because clouds emit at wavelengths that are semi-transparent to greenhouse gases, most notably water vapour. Here we show how temperature and humidity control CRE through competing influences between the mid- and far-infrared. At constant relative humidity, CRE does not decrease with increasing temperature/absolute humidity as expected, but rather is found to be approximately constant for temperatures characteristic of the Arctic. This stability is disrupted if relative humidity varies. Our findings explain observed seasonal and regional variability in Arctic CRE of order 10 W m(-2). With the physical properties of Arctic clouds held constant, we calculate recent increases in CRE of 1-5 W m(-2) in autumn and winter, which are projected to reach 5-15 W m(-2) by 2050, implying increased sensitivity of the surface to clouds.

Humidity trends imply increased sensitivity to clouds in a warming Arctic

PubMed Central

Cox, Christopher J.; Walden, Von P.; Rowe, Penny M.; Shupe, Matthew D.

2015-01-01

Infrared radiative processes are implicated in Arctic warming and sea-ice decline. The infrared cloud radiative effect (CRE) at the surface is modulated by cloud properties; however, CRE also depends on humidity because clouds emit at wavelengths that are semi-transparent to greenhouse gases, most notably water vapour. Here we show how temperature and humidity control CRE through competing influences between the mid- and far-infrared. At constant relative humidity, CRE does not decrease with increasing temperature/absolute humidity as expected, but rather is found to be approximately constant for temperatures characteristic of the Arctic. This stability is disrupted if relative humidity varies. Our findings explain observed seasonal and regional variability in Arctic CRE of order 10 W m−2. With the physical properties of Arctic clouds held constant, we calculate recent increases in CRE of 1–5 W m−2 in autumn and winter, which are projected to reach 5–15 W m−2 by 2050, implying increased sensitivity of the surface to clouds. PMID:26657324

Atlas of the Earth's radiation budget as measured by Nimbus-7: May 1979 to May 1980

NASA Technical Reports Server (NTRS)

Kyle, H. Lee; Hucek, Richard R.; Vallette, Brenda J.

1991-01-01

This atlas describes the seasonal changes in the Earth's radiation budget for the 13-month period, May 1979 to May 1980. It helps to illustrate the strong feedback mechanisms by which the Earth's climate interacts with the top-of-the-atmosphere insolation to modify the energy that various regions absorb from the Sun. Cloud type and cloud amount, which are linked to the surface temperature and the regional climate, are key elements in this interaction. Annual, seasonal, and monthly maps of the albedo, outgoing longwave and net radiation, noontime cloud cover, and mean diurnal surface temperatures are presented. Annual and seasonal net cloud forcing maps are also given. All of the quantities were derived from Nimbus-7 satellite measurements except for the temperatures, which were used in the cloud detection algorithm and came originally from the Air Force 3-dimensional nephanalysis dataset. The seasonal changes are described. The interaction of clouds and the radiation budget is briefly discussed.

Observations of the Global Characteristics and Regional Radiative Effects of Marine Cloud Liquid Water

NASA Technical Reports Server (NTRS)

Greenwald, Thomas J.; Stephens, Graeme L.; Christopher, Sundar A.; Vonder Harr, Thomas H.

1995-01-01

The large-scale spatial distribution and temporal variability of cloud liquid water path (LWP) over the world's oceans and the relationship of cloud LWP to temperature and the radiation budget are investigated using recent satellite measurements from the Special Sensor Microwave/Imager (SSM/I), the Earth Radiation Budget Experiment (ERBE), and the International Satellite Cloud Climatology Project (ISCCP). Observations of cloud liquid water on a 2.5 deg x 2.5 deg and are used over a 53-month period beginning July 1987 and ending in December 1991. The highest values of cloud liquid water (greater than 0.13 kg/sq m) occur largely along principal routes of northern midlatitude storms and in areas dominated by tropical convection. The zonally averaged structure is distinctly trimodal, where maxima appear in the midlatitudes and near the equator. The average marine cloud LWP over the globe is estimated to be about 0.113 kg/sq m. Its highest seasonal variability is typically between 15% and 25% of the annual mean but in certain locations can exceed 30%. Comparisons of cloud LWP to temperature for low clouds during JJA and DJF of 1990 show significant positive correlations at colder temperatures and negative correlations at warmer temperatures. The correlations also exhibit strong seasonal and regional variation. Coincident and collocated observations of cloud LWP from the SSM/I and albedo measurements from the Earth Radiation Budget Satellite (ERBS) and the NOAA-10 satellite are compared for low clouds in the North Pacific and North Atlantic. The observed albedo-LWP relationships correspond reasonably well with theory, where the average cloud effective radius (r(sub e)) is 11.1 microns and the standard deviation is 5.2 microns. The large variability in the inferred values of r(sub e) suggests that other factors may be important in the albedo-LWP relationships. In terms of the effect of the LWP on the net cloud forcing, the authors find that a 0.05 kg/sq m increase in LWP (for LWP less than 0.2 kg/sq m) results in a -25 W/sq m change in the net cloud forcing at a solar zenith angle of 75 deg.

THERMTRAJ: A FORTRAN program to compute the trajectory and gas film temperatures of zero pressure balloons

NASA Technical Reports Server (NTRS)

Horn, W. J.; Carlson, L. A.

1983-01-01

A FORTRAN computer program called THERMTRAJ is presented which can be used to compute the trajectory of high altitude scientific zero pressure balloons from launch through all subsequent phases of the balloon flight. In addition, balloon gas and film temperatures can be computed at every point of the flight. The program has the ability to account for ballasting, changes in cloud cover, variable atmospheric temperature profiles, and both unconditional valving and scheduled valving of the balloon gas. The program was verified for an extensive range of balloon sizes (from 0.5 to 41.47 million cubic feet). Instructions on program usage, listing of the program source deck, input data and printed and plotted output for a verification case are included.

Atmospheric circulation of brown dwarfs and directly imaged extrasolar giant planets with active clouds

NASA Astrophysics Data System (ADS)

Tan, Xianyu; Showman, Adam

2016-10-01

Observational evidence have suggested active meteorology in the atmospheres of brown dwarfs (BDs) and directly imaged extrasolar giant planets (EGPs). In particular, a number of surveys for brown dwarfs showed that near-IR brightness variability is common for L and T dwarfs. Directly imaged EGPs share similar observations, and can be viewed as low-gravity versions of BDs. Clouds are believed to play the major role in shaping the thermal structure, dynamics and near-IR flux of these atmospheres. So far, only a few studies have been devoted to atmospheric circulation and the implications for observations of BDs and directly EGPs, and yet no global model includes a self-consistent active cloud formation. Here we present preliminary results from the first global circulation model applied to BDs and directly imaged EGPs that can properly treat absorption and scattering of radiation by cloud particles. Our results suggest that horizontal temperature differences on isobars can reach up to a few hundred Kelvins, with typical horizontal length scale of the temperature and cloud patterns much smaller than the radius of the object. The combination of temperature anomaly and cloud pattern can result in moderate disk-integrated near-IR flux variability. Wind speeds can reach several hundred meters per second in cloud forming layers. Unlike Jupiter and Saturn, we do not observe stable zonal jet/banded patterns in our simulations. Instead, our simulated atmospheres are typically turbulent and dominated by transient vortices. The circulation is sensitive to the parameterized cloud microphysics. Under some parameter combinations, global-scale atmospheric waves can be triggered and maintained. These waves induce global-scale temperature anomalies and cloud patterns, causing large (up to several percent) disk-integrated near-IR flux variability. Our results demonstrate that the commonly observed near-IR brightness variability for BDs and directly imaged EGPs can be explained by the typical cloud-induced turbulent circulation, and in particular, the large flux variability for some objects can be attributed to the global-scale patterns of temperature anomaly and cloud formation caused by atmospheric waves.

Cloud properties inferred from 8-12 micron data

NASA Technical Reports Server (NTRS)

Strabala, Kathleen I.; Ackerman, Steven A.; Menzel, W. Paul

1994-01-01

A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.

Infrared radiative transfer through a regular array of cuboidal clouds

NASA Technical Reports Server (NTRS)

HARSHVARDHAN; Weinman, J. A.

1981-01-01

Infrared radiative transfer through a regular array of cuboidal clouds is studied and the interaction of the sides of the clouds with each other and the ground is considered. The theory is developed for black clouds and is extended to scattering clouds using a variable azimuth two-stream approximation. It is shown that geometrical considerations often dominate over the microphysical aspects of radiative transfer through the clouds. For example, the difference in simulated 10 micron brightness temperature between black isothermal cubic clouds and cubic clouds of optical depth 10, is less than 2 deg for zenith angles less than 50 deg for all cloud fractions when viewed parallel to the array. The results show that serious errors are made in flux and cooling rate computations if broken clouds are modeled as planiform. Radiances computed by the usual practice of area-weighting cloudy and clear sky radiances are in error by 2 to 8 K in brightness temperature for cubic clouds over a wide range of cloud fractions and zenith angles. It is also shown that the lapse rate does not markedly affect the exiting radiances for cuboidal clouds of unit aspect ratio and optical depth 10.

Modeling CO, CO2, and H2O Ice Abundances in the Envelopes of Young Stellar Objects in the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Pauly, Tyler; Garrod, Robin T.

2018-02-01

Massive young stellar objects (MYSOs) in the Magellanic Clouds show infrared absorption features corresponding to significant abundances of CO, CO2, and H2O ice along the line of sight, with the relative abundances of these ices differing between the Magellanic Clouds and the Milky Way. CO ice is not detected toward sources in the Small Magellanic Cloud, and upper limits put its relative abundance well below sources in the Large Magellanic Cloud and the Milky Way. We use our gas-grain chemical code MAGICKAL, with multiple grain sizes and grain temperatures, and further expand it with a treatment for increased interstellar radiation field intensity to model the elevated dust temperatures observed in the MCs. We also adjust the elemental abundances used in the chemical models, guided by observations of H II regions in these metal-poor satellite galaxies. With a grid of models, we are able to reproduce the relative ice fractions observed in MC MYSOs, indicating that metal depletion and elevated grain temperature are important drivers of the MYSO envelope ice composition. Magellanic Cloud elemental abundances have a subgalactic C/O ratio, increasing H2O ice abundances relative to the other ices; elevated grain temperatures favor CO2 production over H2O and CO. The observed shortfall in CO in the Small Magellanic Cloud can be explained by a combination of reduced carbon abundance and increased grain temperatures. The models indicate that a large variation in radiation field strength is required to match the range of observed LMC abundances. CH3OH abundance is found to be enhanced in low-metallicity models, providing seed material for complex organic molecule formation in the Magellanic Clouds.

Comparison of roadway roughness derived from LIDAR and SFM 3D point clouds.

DOT National Transportation Integrated Search

2015-10-01

This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point : clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially : cont...

The evaluation of GCMs and a new cloud parameterisation using satellite and in-situ data as part of a Climate Process Team

NASA Astrophysics Data System (ADS)

Grosvenor, D. P.; Wood, R.

2012-12-01

As part of one of the Climate Process Teams (CPTs) we have been testing the implementation of a new cloud parameterization into the CAM5 and AM3 GCMs. The CLUBB parameterization replaces all but the deep convection cloud scheme and uses an innovative PDF based approach to diagnose cloud water content and turbulence. We have evaluated the base models and the CLUBB parameterization in the SE Pacific stratocumulus region using a suite of satellite observation metrics including: Liquid Water Path (LWP) measurements from AMSRE; cloud fractions from CloudSat/CALIPSO; droplet concentrations (Nd) and Cloud Top Temperatures from MODIS; CloudSat precipitation; and relationships between Estimated Inversion Strength (calculated from AMSRE SSTs, Cloud Top Temperatures from MODIS and ECMWF re-analysis fields) and cloud fraction. This region has the advantage of an abundance of in-situ aircraft observations taken during the VOCALS campaign, which is facilitating the diagnosis of the model problems highlighted by the model evaluation. This data has also been recently used to demonstrate the reliability of MODIS Nd estimates. The satellite data needs to be filtered to ensure accurate retrievals and we have been careful to apply the same screenings to the model fields. For example, scenes with high cloud fractions and with output times near to the satellite overpass times can be extracted from the model for a fair comparison with MODIS Nd estimates. To facilitate this we have been supplied with instantaneous model output since screening would not be possible based on time averaged data. We also have COSP satellite simulator output, which allows a fairer comparison between satellite and model. For example, COSP cloud fraction is based upon the detection threshold of the satellite instrument in question. These COSP fields are also used for the model output filtering just described. The results have revealed problems with both the base models and the versions with the CLUBB parameterization. The CAM5 model produces realistic near-coast cloud cover, but too little further west in the stratocumulus to cumulus regions. The implementation of CLUBB has vastly improved this situation with cloud cover that is very similar to that observed. CLUBB also improves the Nd field in CAM5 by producing realistic near-coast increases and by removing high Nd values associated with the detrainment of droplets by cumulus clouds. AM3 has a lack of stratocumulus cloud near the South American coast and has much lower droplet concentrations than observed. VOCALS measurements showed that sulfate mass loadings were generally too high in both base models, whereas CCN concentrations were too low. This suggests a problem with the mass distribution partitioning of sulfate that is being investigated. Diurnal and seasonal comparisons have been very illuminating. CLUBB produces very little diurnal variation in LWP, but large variations in precipitation rates. This is likely to point to problems that are now being addressed by the modeling part of the CPT team, creating an iterative workflow process between the model developers and the model testers, which should facilitate efficient parameterization improvement. We will report on the latest developments of this process.

D Modeling of Components of a Garden by Using Point Cloud Data

NASA Astrophysics Data System (ADS)

Kumazakia, R.; Kunii, Y.

2016-06-01

Laser measurement is currently applied to several tasks such as plumbing management, road investigation through mobile mapping systems, and elevation model utilization through airborne LiDAR. Effective laser measurement methods have been well-documented in civil engineering, but few attempts have been made to establish equally effective methods in landscape engineering. By using point cloud data acquired through laser measurement, the aesthetic landscaping of Japanese gardens can be enhanced. This study focuses on simple landscape simulations for pruning and rearranging trees as well as rearranging rocks, lanterns, and other garden features by using point cloud data. However, such simulations lack concreteness. Therefore, this study considers the construction of a library of garden features extracted from point cloud data. The library would serve as a resource for creating new gardens and simulating gardens prior to conducting repairs. Extracted garden features are imported as 3ds Max objects, and realistic 3D models are generated by using a material editor system. As further work toward the publication of a 3D model library, file formats for tree crowns and trunks should be adjusted. Moreover, reducing the size of created models is necessary. Models created using point cloud data are informative because simply shaped garden features such as trees are often seen in the 3D industry.

Extractive biodegradation and bioavailability assessment of phenanthrene in the cloud point system by Sphingomonas polyaromaticivorans.

PubMed

Pan, Tao; Deng, Tao; Zeng, Xinying; Dong, Wei; Yu, Shuijing

2016-01-01

The biological treatment of polycyclic aromatic hydrocarbons is an important issue. Most microbes have limited practical applications because of the poor bioavailability of polycyclic aromatic hydrocarbons. In this study, the extractive biodegradation of phenanthrene by Sphingomonas polyaromaticivorans was conducted by introducing the cloud point system. The cloud point system is composed of a mixture of (40 g/L) Brij 30 and Tergitol TMN-3, which are nonionic surfactants, in equal proportions. After phenanthrene degradation, a higher wet cell weight and lower phenanthrene residue were obtained in the cloud point system than that in the control system. According to the results of high-performance liquid chromatography, the residual phenanthrene preferred to partition from the dilute phase into the coacervate phase. The concentration of residual phenanthrene in the dilute phase (below 0.001 mg/L) is lower than its solubility in water (1.18 mg/L) after extractive biodegradation. Therefore, dilute phase detoxification was achieved, thus indicating that the dilute phase could be discharged without causing phenanthrene pollution. Bioavailability was assessed by introducing the apparent logP in the cloud point system. Apparent logP decreased significantly, thus indicating that the bioavailability of phenanthrene increased remarkably in the system. This study provides a potential application of biological treatment in water and soil contaminated by phenanthrene.

Quantitative evaluation for small surface damage based on iterative difference and triangulation of 3D point cloud

NASA Astrophysics Data System (ADS)

Zhang, Yuyan; Guo, Quanli; Wang, Zhenchun; Yang, Degong

2018-03-01

This paper proposes a non-contact, non-destructive evaluation method for the surface damage of high-speed sliding electrical contact rails. The proposed method establishes a model of damage identification and calculation. A laser scanning system is built to obtain the 3D point cloud data of the rail surface. In order to extract the damage region of the rail surface, the 3D point cloud data are processed using iterative difference, nearest neighbours search and a data registration algorithm. The curvature of the point cloud data in the damage region is mapped to RGB color information, which can directly reflect the change trend of the curvature of the point cloud data in the damage region. The extracted damage region is divided into three prism elements by a method of triangulation. The volume and mass of a single element are calculated by the method of geometric segmentation. Finally, the total volume and mass of the damage region are obtained by the principle of superposition. The proposed method is applied to several typical injuries and the results are discussed. The experimental results show that the algorithm can identify damage shapes and calculate damage mass with milligram precision, which are useful for evaluating the damage in a further research stage.

Electron temperatures within magnetic clouds between 2 and 4 AU: Voyager 2 observations

NASA Astrophysics Data System (ADS)

Sittler, E. C.; Burlaga, L. F.

1998-08-01

We have performed an analysis of Voyager 2 plasma electron observations within magnetic clouds between 2 and 4 AU identified by Burlaga and Behannon [1982]. The analysis has been confined to three of the magnetic clouds identified by Burlaga and Behannon that had high-quality data. The general properties of the plasma electrons within a magnetic cloud are that (1) the moment electron temperature anticorrelates with the electron density within the cloud, (2) the ratio Te/Tp tends to be >1, and (3) on average, Te/Tp~7.0. All three results are consistent with previous electron observations within magnetic clouds. Detailed analyses of the core and halo populations within the magnetic clouds show no evidence of either an anticorrelation between the core temperature TC and the electron density Ne or an anticorrelation between the halo temperature TH and the electron density. Within the magnetic clouds the halo component can contribute more than 50% of the electron pressure. The anticorrelation of Te relative to Ne can be traced to the density of the halo component relative to the density of the core component. The core electrons dominate the electron density. When the density goes up, the halo electrons contribute less to the electron pressure, so we get a lower Te. When the electron density goes down, the halo electrons contribute more to the electron pressure, and Te goes up. We find a relation between the electron pressure and density of the form Pe=αNeγ with γ~0.5.

Low cloud investigations for project FIRE: Island studies of cloud properties, surface radiation, and boundary layer dynamics. A simulation of the reflectivity over a stratocumulus cloud deck by the Monte Carlo method. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Ackerman, Thomas P.; Lin, Ruei-Fong

1993-01-01

The radiation field over a broken stratocumulus cloud deck is simulated by the Monte Carlo method. We conducted four experiments to investigate the main factor for the observed shortwave reflectively over the FIRE flight 2 leg 5, in which reflectivity decreases almost linearly from the cloud center to cloud edge while the cloud top height and the brightness temperature remain almost constant through out the clouds. From our results, the geometry effect, however, did not contribute significantly to what has been observed. We found that the variation of the volume extinction coefficient as a function of its relative position in the cloud affects the reflectivity efficiently. Additional check of the brightness temperature of each experiment also confirms this conclusion. The cloud microphysical data showed some interesting features. We found that the cloud droplet spectrum is nearly log-normal distributed when the clouds were solid. However, whether the shift of cloud droplet spectrum toward the larger end is not certain. The decrease of number density from cloud center to cloud edges seems to have more significant effects on the optical properties.

Comparison of DSMs acquired by terrestrial laser scanning, UAV-based aerial images and ground-based optical images at the Super-Sauze landslide

NASA Astrophysics Data System (ADS)

Rothmund, Sabrina; Niethammer, Uwe; Walter, Marco; Joswig, Manfred

2013-04-01

In recent years, the high-resolution and multi-temporal 3D mapping of the Earth's surface using terrestrial laser scanning (TLS), ground-based optical images and especially low-cost UAV-based aerial images (Unmanned Aerial Vehicle) has grown in importance. This development resulted from the progressive technical improvement of the imaging systems and the freely available multi-view stereo (MVS) software packages. These different methods of data acquisition for the generation of accurate, high-resolution digital surface models (DSMs) were applied as part of an eight-week field campaign at the Super-Sauze landslide (South French Alps). An area of approximately 10,000 m² with long-term average displacement rates greater than 0.01 m/day has been investigated. The TLS-based point clouds were acquired at different viewpoints with an average point spacing between 10 to 40 mm and at different dates. On these days, more than 50 optical images were taken on points along a predefined line on the side part of the landslide by a low-cost digital compact camera. Additionally, aerial images were taken by a radio-controlled mini quad-rotor UAV equipped with another low-cost digital compact camera. The flight altitude ranged between 20 m and 250 m and produced a corresponding ground resolution between 0.6 cm and 7 cm. DGPS measurements were carried out as well in order to geo-reference and validate the point cloud data. To generate unscaled photogrammetric 3D point clouds from a disordered and tilted image set, we use the widespread open-source software package Bundler and PMVS2 (University of Washington). These multi-temporal DSMs are required on the one hand to determine the three-dimensional surface deformations and on the other hand it will be required for differential correction for orthophoto production. Drawing on the example of the acquired data at the Super-Sauze landslide, we demonstrate the potential but also the limitations of the photogrammetric point clouds. To determine the quality of the photogrammetric point cloud, these point clouds are compared with the TLS-based DSMs. The comparison shows that photogrammetric points accuracies are in the range of cm to dm, therefore don't reach the quality of the high-resolution TLS-based DSMs. Further, the validation of the photogrammetric point clouds reveals that some of them have internal curvature effects. The advantage of the photogrammetric 3D data acquisition is the use of low-cost equipment and less time-consuming data collection in the field. While the accuracy of the photogrammetric point clouds is not as high as TLS-based DSMs, the advantages of the former method are seen when applied in areas where dm-range is sufficient.

The thermodynamic and dynamical features of double front structures during 21 31 July 1998 in China

NASA Astrophysics Data System (ADS)

Zhou, Yushu; Deng, Guo; Lei, Ting; Ju, Jianhua

2005-11-01

The daily 1° × 1° data of the Aviation (AVN) model, the black body temperature (TBB) data of cloud top, and cloud images by geostationary meteorological satellite (GMS) are used to identify a dew-point front near the periphery of the western Pacific subtropical high (WPSH). The results clearly demonstrate the existence of the dew-point front, and its thermodynamic and dynamic structural characteristics are analyzed in detail. The dew-point front is a transitional belt between the moist southwest monsoon flow and the dry adiabatic sinking flow near the WPSH, manifested by a large horizontal moisture gradient in the mid-lower troposphere and conjugated with the mei-yu front to form a predominant double-front structure associated with intense rainfall in the mei-yu period. The mei-yu front is located between 30° and 35°N, vertically extends from the ground level to the upper level and shifts northward. The dew-point front is to the south of the mei-yu front and lies up against the periphery of the WPSH. Generally, it is located between 850 hPa and 500 hPa. On the dew-point front side, the southwesterly prevails at the lower level and the northeasterly at the upper level; this wind distribution is different from that on the mei-yu front side. Vertical ascending motion exists between the two fronts, and there are descending motions on the north side of the mei-yu front and on the south side of the dew-point front, which form a secondary circulation. The dynamics of the double fronts also have some interesting features. At the lower level, positive vertical vorticity and obvious convergence between the two fronts are clearly identified. At the mid-lower level, negative local change of the divergence (corresponding to increasing convergence) is often embedded in the two fronts or against the mei-yu front. Most cloud clusters occur between the two fronts and propagate down stream in a wave-like manner.

A Laboratory Study on the Phase Transition for Polar Stratospheric Cloud Particles

NASA Technical Reports Server (NTRS)

Teets, Edward H., Jr.

1997-01-01

The nucleation and growth of different phases of simulated polar stratospheric cloud (PSC) particles were investigated in the laboratory. Solutions and mixtures of solutions at concentrations 1 to 5 m (molality) of ammonium sulfate, ammonium bisulfate, sodium chloride, sulfuric acid, and nitric acid were supercooled to prescribed temperatures below their equilibrium melting point. These solutions were contained in small diameter glass tubing of volumes ranging from 2.6 to 0.04 ml. Samples were nucleated by insertion of an ice crystal, or in some cases by a liquid nitrogen cooled wire. Crystallization velocities were determined by timing the crystal growth front passages along the glass tubing. Solution mixtures containing aircraft exhaust (soot) were also examined. Crystallization rates increased as deltaT2, where deltaT is the supercooling for weak solutions (2 m or less). The higher concentrated solutions (greater than 3 m) showed rates significantly less than deltaT2. This reduced rate suggested an onset of a glass phase. Results were applied to the nucleation of highly concentrated solutions at various stages of polar stratospheric cloud development within the polar stratosphere.

Cloud Condensation Nuclei in Cumulus Humilis - Selected Case Study During the CHAPS Campaign

NASA Astrophysics Data System (ADS)

Yu, X.; Berg, L. K.; Berkowitz, C. M.; Alexander, M. L.; Lee, Y.; Laskin, A.; Ogren, J. A.; Andrews, B.

2009-12-01

The Cumulus Humilis Aerosol Processing Study (CHAPS) provided a unique opportunity to study aerosol and cloud processing. Clouds play an active role in the processing and cycling of atmospheric constituents. Gases and particles can partition to cloud droplets by absorption and condensation as well as activation and pact scavenging. The Department of Energy (DOE) G-1 aircraft was used as one of the main platforms in CHAPS. Flight tracks were designed and implemented to characterize freshly emitted aerosols on cloud top and cloud base as well as with cloud, i.e., cumulus humilis (or fair-weather cumulus), in the vicinity of Oklahoma City. Measurements of interstitial aerosols and residuals of activated condensation cloud nuclei were conducted simultaneously. The interstitial aerosols were determined downstream of an isokinetic inlet; and the activated particles downstream of a counter-flow virtual impactor (CVI). The sampling line to the Aerodyne Aerosol Mass Spectrometer was switched between the isokinetic inlet and the CVI to allow characterization of interstitial particles out of clouds in contrast to particles activated in clouds. Trace gases including ozone, carbon monoxide, sulfur dioxide, and a series of volatile organic compounds (VOCs) were also measured as were key meteorological state parameters including liquid water content, cloud drop size, and dew point temperature were measured. This work will focus on studying CCN properties in cumulus humilis. Several approaches will be taken. The first is single particle analysis of particles collected by the Time-Resolved Aerosol Sampler (TRAC) by SEM/TEM coupled with EDX. We will specifically look into differences in particle properties such as chemical composition and morphology between activated and interstitial ones. The second analysis will link in situ measurements with the snap shots observations by TRAC. For instance, by looking into the characteristic m/z obtained by AMS vs. CO or isoprene, one can gain more insight into the role of primary and secondary organic aerosols in CCNs and background aerosols. Combined with observations of cloud properties, an improved picture of CCN activation in cumulus humilis can be made.

Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.

Itinerant ferromagnetism in ultracold Fermi gases

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

Heiselberg, H.

2011-05-15

Itinerant ferromagnetism in cold Fermi gases with repulsive interactions is studied applying the Jastrow-Slater approximation generalized to finite polarization and temperature. For two components at zero temperature, a second-order transition is found at ak{sub F}{approx_equal}0.90 compatible with results of quantum-Monte-Carlo (QMC) calculations. Thermodynamic functions and observables, such as the compressibility and spin susceptibility and the resulting fluctuations in number and spin, are calculated. For trapped gases, the resulting cloud radii and kinetic energies are calculated and compared to recent experiments. Spin-polarized systems are recommended for effective separation of large ferromagnetic domains. Collective modes are predicted and tricritical points are calculatedmore » for multicomponent systems.« less

Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

NASA Astrophysics Data System (ADS)

Xu, Y.; Boerner, R.; Yao, W.; Hoegner, L.; Stilla, U.

2017-09-01

For obtaining a full coverage of 3D scans in a large-scale urban area, the registration between point clouds acquired via terrestrial laser scanning (TLS) is normally mandatory. However, due to the complex urban environment, the automatic registration of different scans is still a challenging problem. In this work, we propose an automatic marker free method for fast and coarse registration between point clouds using the geometric constrains of planar patches under a voxel structure. Our proposed method consists of four major steps: the voxelization of the point cloud, the approximation of planar patches, the matching of corresponding patches, and the estimation of transformation parameters. In the voxelization step, the point cloud of each scan is organized with a 3D voxel structure, by which the entire point cloud is partitioned into small individual patches. In the following step, we represent points of each voxel with the approximated plane function, and select those patches resembling planar surfaces. Afterwards, for matching the corresponding patches, a RANSAC-based strategy is applied. Among all the planar patches of a scan, we randomly select a planar patches set of three planar surfaces, in order to build a coordinate frame via their normal vectors and their intersection points. The transformation parameters between scans are calculated from these two coordinate frames. The planar patches set with its transformation parameters owning the largest number of coplanar patches are identified as the optimal candidate set for estimating the correct transformation parameters. The experimental results using TLS datasets of different scenes reveal that our proposed method can be both effective and efficient for the coarse registration task. Especially, for the fast orientation between scans, our proposed method can achieve a registration error of less than around 2 degrees using the testing datasets, and much more efficient than the classical baseline methods.

Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

NASA Astrophysics Data System (ADS)

Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

2000-12-01

The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air temperature.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Properties of an αs-casein-rich casein fraction: influence of dialysis on surface properties, miscibility, and micelle formation.

PubMed

Kessler, Anne; Menéndez-Aguirre, Orquidéa; Hinrichs, Jörg; Stubenrauch, Cosima; Weiss, Jochen

2013-09-01

In this study, the surface tension, miscibility, and particle size distribution of a solution containing an αs-casein (CN)-rich CN fraction (54 wt % αs-CN, 32 wt % β-CN, and 15 wt % κ-CN) were determined at pH 6.6. The nondialyzed CN fraction was compared with a dialyzed one. In the nondialyzed sample, every charge on the protein was compensated by 0.3 charges coming from counterions, whereas in the dialyzed sample, only 0.2 charges could be assigned to each charge on the protein. This relation was determined by calculating the charges at the proteins, taking the measured mineral content into account. The surface tension was measured as a function of the protein concentration by the du Noüy ring method at room temperature. Results indicated alterations in the surface properties after reduction of counterions. The equilibrium surface tension above the critical micelle concentration increased from 40.1×10(-3) to 45×10(-3) N/m, the critical micelle concentration increased from 0.9×10(-4) to 2×10(-3) mol/L, and the minimal area occupied per molecule at the surface increased from 2.4×10(-18) to 4.6×10(-18) m(2). Cloud points were determined by measuring the absorbance of CN solutions as a function of the temperature. The cloud points were found to be concentration dependent and had a minimum at 0.2 wt % at 34°C for nondialyzed CN and at 0.25 wt % at 28°C for dialyzed CN, again demonstrating the influence of counterion reduction. Below the cloud point, a micellar phase was found to exist. The hydrodynamic diameter of the micelles were characterized by dynamic light scattering in both auto- and cross-correlation mode. However, no influence of reduction in counterions could be observed, possibly due to the fact that dynamic light scattering is not a suitable method for this type of system. The presence of self-assembled structures was verified by freeze-fracture electron microscopy. The observed differences between dialyzed and nondialyzed samples were explained by changes in the counterion cloud surrounding the proteins. Consequently, the electrostatic interactions between as well as within the CN are altered by dialysis, which, in turn, affects the behavior at the surface as well as the properties in the solution. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Influence of Microphysical Cloud Parameterization on Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Gasiewski, Albin J.; Wang, James R.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The microphysical parameterization of clouds and rain-cells plays a central role in atmospheric forward radiative transfer models used in calculating passive microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density., shape, and dielectric constant. This study identifies the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Cloud parameterizations for wideband (6-410 GHz observations of baseline brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a five-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that, enlarging the rain drop size or adding water to the partly Frozen hydrometeor mix warms brightness temperatures by up to .55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture LA Experiment (CAMEX 3) brightness temperatures shows that in general all but, two parameterizations produce calculated T(sub B)'s that fall within the observed clear-air minima and maxima. The exceptions are for parameterizations that, enhance the scattering characteristics of frozen hydrometeors.

Pre-activation of aerosol particles by ice preserved in pores

NASA Astrophysics Data System (ADS)

Marcolli, Claudia

2017-02-01

Pre-activation denotes the capability of particles or materials to nucleate ice at lower relative humidities or higher temperatures compared to their intrinsic ice nucleation efficiency after having experienced an ice nucleation event or low temperature before. This review presumes that ice preserved in pores is responsible for pre-activation and analyses pre-activation under this presumption. Idealized trajectories of air parcels are used to discuss the pore characteristics needed for ice to persist in pores and to induce macroscopic ice growth out of the pores. The pore width needed to keep pores filled with water decreases with decreasing relative humidity as described by the inverse Kelvin equation. Thus, narrow pores remain filled with ice well below ice saturation. However, the smaller the pore width, the larger the melting and freezing point depressions within the pores. Therefore, pre-activation due to pore ice is constrained by the melting of ice in narrow pores and the sublimation of ice from wide pores imposing restrictions on the temperature and relative humidity range of pre-activation for cylindrical pores. Ice is better protected in ink-bottle-shaped pores with a narrow opening leading to a large cavity. However, whether pre-activation is efficient also depends on the capability of ice to grow macroscopically, i.e. out of the pore. A strong effect of pre-activation is expected for swelling pores, because at low relative humidity (RH) their openings narrow and protect the ice within them against sublimation. At high relative humidities, they open up and the ice can grow to macroscopic size and form an ice crystal. Similarly, ice protected in pockets is perfectly sheltered against sublimation but needs the dissolution of the surrounding matrix to be effective. Pores partially filled with condensable material may also show pre-activation. In this case, complete filling occurs at lower RH than for empty pores and freezing shifts to lower temperatures.Pre-activation experiments confirm that materials susceptible to pre-activation are indeed porous. Pre-activation was observed for clay minerals like illite, kaolinite, and montmorillonite with inherent porosity. The largest effect was observed for the swelling clay mineral montmorillonite. Some materials may acquire porosity, depending on the formation and processing conditions. Particles of CaCO3, meteoritic material, and volcanic ash showed pre-activation for some samples or in some studies but not in other ones. Quartz and silver iodide were not susceptible to pre-activation.Atmospheric relevance of pre-activation by ice preserved in pores may not be generally given but depend on the atmospheric scenario. Lower-level cloud seeding by pre-activated particles released from high-level clouds crucially depends on the ability of pores to retain ice at the relative humidities and temperatures of the air masses they pass through. Porous particles that are recycled in wave clouds may show pre-activation with subsequent ice growth as soon as ice saturation is exceeded after having passed a first cloud event. Volcanic ash particles and meteoritic material likely influence ice cloud formation by pre-activation. Therefore, the possibility of pre-activation should be considered when ice crystal number densities in clouds exceed the number of ice-nucleating particles measured at the cloud forming temperature.

Cloud Modeling

NASA Technical Reports Server (NTRS)

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

2001-01-01

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