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Sample records for 3d cloud resolving

  1. 3D Atmospheric Radiative Transfer for Cloud System-Resolving Models: Forward Modelling and Observations

    SciTech Connect

    Howard Barker; Jason Cole

    2012-05-17

    Utilization of cloud-resolving models and multi-dimensional radiative transfer models to investigate the importance of 3D radiation effects on the numerical simulation of cloud fields and their properties.

  2. Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

  3. Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

  4. Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

  5. Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

  6. Cloud-resolving component in the quasi-3D multi-scale modeling framework

    NASA Astrophysics Data System (ADS)

    Jung, Joon-Hee; Arakawa, Akio

    2010-05-01

    A quasi-3D multi-scale modeling framework (Q3D MMF), which combines a GCM with a Q3D CRM, is an attempt to include three dimensional cloud effects in a GCM without necessarily using a global cloud-resolving model. The horizontal domain of the Q3D CRM consists of two perpendicular sets of channels crossing at the center of a GCM grid box, each of which includes two grid-point arrays. Through coupling this structure with a GCM, the whole system of the Q3D MMF can converge to a fully 3D global CRM as the GCM's resolution is refined. Consequently, the horizontal resolution of the GCM can be freely chosen depending on the objective of application. However, due to the use of very narrow channels for the cloud-resolving component, its prediction algorithm must be specially designed. As a step in developing a Q3D MMF, we have first constructed a prediction algorithm for the Q3D CRM applying a 3D anelastic vector vorticity equation model to the Q3D network of grid points. Preliminary tests of the Q3D CRM have been performed for an idealized small domain. Comparing the results with those of the straightforward application of a 3D CRM, it is concluded that the Q3D CRM can reproduce most of the important statistics of the 3D solutions and the MMF based on the Q3D CRM will be a useful framework for climate modeling. This paper presents an outline of the Q3D algorithm and highlights of the results.

  7. Tropical Oceanic Precipitation Processes over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.- K.; Johnson, D.

    1998-01-01

    stratiform regions; (3) the cloud (upward-downward) mass fluxes in convective and stratiform regions; (4) characteristics of clouds (such as cloud size, updraft intensity and cloud lifetime) and the comparison of clouds with Radar observations. Differences and similarities in organization of convection between simulated 2D and 3D cloud systems. Preliminary results indicated that there is major differences between 2D and 3D simulated stratiform rainfall amount and convective updraft and downdraft mass fluxes.

  8. Tropical Oceanic Precipitation Processes over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.- K.; Johnson, D.

    1998-01-01

    stratiform regions; (3) the cloud (upward-downward) mass fluxes in convective and stratiform regions; (4) characteristics of clouds (such as cloud size, updraft intensity and cloud lifetime) and the comparison of clouds with Radar observations. Differences and similarities in organization of convection between simulated 2D and 3D cloud systems. Preliminary results indicated that there is major differences between 2D and 3D simulated stratiform rainfall amount and convective updraft and downdraft mass fluxes.

  9. Exploratory Analysis Of The 3D Cloud Resolving Model Simulations of TOGA COARE: Preliminary Results

    NASA Astrophysics Data System (ADS)

    Mendes, S.; Bretherton, C.

    2007-12-01

    Global climate model studies suggest that cumulus momentum transport (CMT) in tropical oceanic convective cloud systems plays a significant role in the tropical mean circulation and transient variability. CMT is difficult to measure directly and can depend on the detailed structure and organization of the convection. Yet there have been comparatively few evaluations of CMT parameterizations and the assumptions underlying them using 3D cloud resolving model (CRM) simulations. We have analyzed CMT in a four month 3D 64x64x64 gridpoint CRM simulation of TOGA COARE with 1 km horizontal resolution. An additional 256x256x64 large-domain simulation was performed for a 10 day subperiod with strong convection combined with substantial mean vertical zonal wind shear, conditions favorably for strong CMT. Both simulations were identically forced with prescribed vertical motion, horizontal temperature and moisture advection, and relaxation of the domain-mean wind profile to observations on a one-hour timescale. Both were initialized with small amplitude white noise, but spun up realistic convection in less than a day. The domain-mean CMT in the small and large domain simulations for the 10-day common simulation period was compared. The two simulations showed remarkably similar CMT profiles on daily-mean timescales, suggesting that mesoscale contributions to CMT of scales greater than 64 km were small. The skill of a downgradient mixing-length parameterization CMT = Mc*L*DU/Dz was also tested. Here , Mc is convective mass flux, dU/dz is mean vertical shear, and L is a mixing length for updraft zonal velocity perturbations associated with entrainment and horizontal pressure gradient accelerations. This was done by regressing CMT at each height was regressed against Mc*DU/Dz at the same height across all 3D model snapshots over the 10 days. The correlation coefficient describes the accuracy of this downgradient parameterization, and L was calculated as the regression slope. In the

  10. Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

  11. Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

  12. Precipitation processes developed during TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999): 3D Cloud Resolving Model Simulation

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.

    2006-01-01

    Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research (NCAR), NOAA GFDL, the U.K. Met. Office, Colorado State University and NASA Goddard Space Flight Center. An improved 3D Goddard Cumulus Ensemble (GCE) model was recently used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (september 1-7, 1974), SCSMEX (May 18-26, June 2-11, 1998) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 by 512 km domain and 41 vertical layers. The major objectives of this paper are: (1) to identify the differences and similarities in the simulated precipitation processes and their associated surface and water energy budgets in TOGA COARE, GATE, KWAJEX, and SCSMEX, and (2) to asses the impact of microphysics, radiation budget and surface fluxes on the organization of convection in tropics.

  13. Precipitation Processes Developed During ARM (1997), TOGA COARE (1992) GATE (1974), SCSMEX (1998), and KWAJEX (1999): Consistent 3D, Semi-3D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.; Hou, A.; Atlas, R.; Starr, D.; Sud, Y.

    2003-01-01

    Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D) have been used to study the response of clouds to large-scale forcing. IN these 3D simulators, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical clouds systems with large horizontal domains at the National Center of Atmospheric Research (NCAR) and at NASA Goddard Space Center. At Goddard, a 3D cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE, GATE, SCSMEX, ARM, and KWAJEX using a 512 by 512 km domain (with 2-km resolution). The result indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D GCE model simulation. The major objective of this paper are: (1) to assess the performance of the super-parametrization technique, (2) calculate and examine the surface energy (especially radiation) and water budget, and (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

  14. Momentum Transport: 2D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2001-01-01

    The major objective of this study is to investigate the momentum budgets associated with several convective systems that developed during the TOGA COARE IOP (west Pacific warm pool region) and GATE (east Atlantic region). The tool for this study is the improved Goddard Cumulas Ensemble (GCE) model which includes a 3-class ice-phase microphysical scheme, explicit cloud radiative interactive processes and air-sea interactive surface processes. The model domain contains 256 x 256 grid points (with 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km) in the vertical. The 2D domain has 1024 grid points. The simulations were performed over a 7-day time period (December 19-26, 1992, for TOGA COARE and September 1-7, 1994 for GATE). Cyclic literal boundary conditions are required for this type of long-term integration. Two well organized squall systems (TOGA, COARE February 22, 1993, and GATE September 12, 1994) were also simulated using the 3D GCE model. Only 9 h simulations were required to cover the life time of the squall systems. the lateral boundary conditions were open for these two squall systems simulations. the following will be examined: (1) the momentum budgets in the convective and stratiform regions, (2) the relationship between momentum transport and cloud organization (i.e., well organized squall lines versus less organized convective), (3) the differences and similarities in momentum transport between 2D and 3D simulated convective systems, and (4) the differences and similarities in momentum budgets between cloud systems simulated with open and cyclic lateral boundary conditions. Preliminary results indicate that there are only small differences between 2D and 3D simulated momentum budgets. Major differences occur, however, between momentum budgets associated with squall systems simulated using different lateral boundary conditions.

  15. Strategy for long-term 3D cloud-resolving simulations over the ARM SGP site and preliminary results

    NASA Astrophysics Data System (ADS)

    Lin, W.; Liu, Y.; Song, H.; Endo, S.

    2011-12-01

    Parametric representations of cloud/precipitation processes continue having to be adopted in climate simulations with increasingly higher spatial resolution or with emerging adaptive mesh framework; and it is only becoming more critical that such parameterizations have to be scale aware. Continuous cloud measurements at DOE's ARM sites have provided a strong observational basis for novel cloud parameterization research at various scales. Despite significant progress in our observational ability, there are important cloud-scale physical and dynamical quantities that are either not currently observable or insufficiently sampled. To complement the long-term ARM measurements, we have explored an optimal strategy to carry out long-term 3-D cloud-resolving simulations over the ARM SGP site using Weather Research and Forecasting (WRF) model with multi-domain nesting. The factors that are considered to have important influences on the simulated cloud fields include domain size, spatial resolution, model top, forcing data set, model physics and the growth of model errors. The hydrometeor advection that may play a significant role in hydrological process within the observational domain but is often lacking, and the limitations due to the constraint of domain-wide uniform forcing in conventional cloud system-resolving model simulations, are at least partly accounted for in our approach. Conventional and probabilistic verification approaches are employed first for selected cases to optimize the model's capability of faithfully reproducing the observed mean and statistical distributions of cloud-scale quantities. This then forms the basis of our setup for long-term cloud-resolving simulations over the ARM SGP site. The model results will facilitate parameterization research, as well as understanding and dissecting parameterization deficiencies in climate models.

  16. Precipitation Processes developed during ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999), Consistent 2D, semi-3D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Hou, A.; Atlas, R.; Starr, D.; Sud, Y.

    2003-01-01

    Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique (i.e. is 2D or semi-3D CRM appropriate for the super-parameterization?); (2) calculate and examine the surface energy (especially radiation) and water budgets; (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

  17. Description and first results of an explicit electrical scheme in a 3D cloud resolving model

    NASA Astrophysics Data System (ADS)

    Barthe, Christelle; Molinié, Gilles; Pinty, Jean-Pierre

    2005-07-01

    The three-dimensional non-hydrostatic mesoscale model MésoNH of the French community offers the numerical environment to develop a cloud electrification scheme in a consistent way with the original mixed phase microphysical scheme. The charge separation mechanisms are entirely due to non-inductive processes and result from elastic ice-snow, ice-graupel and snow-graupel collisions. The electric charges carried by each of the five hydrometeor categories are transported along the airflow and are exchanged according to the various microphysical mass transfer rates but assuming a power law distribution of the individual charges as a function of the particle size. The electric field is diagnosed at each time step after integrating the electric potential induced by a net charge density in the Poisson equation. Finally, a lightning ash is triggered when the electric field locally steps over a given threshold. It propagates in two opposite directions until the magnitude of the electric field falls below a prescribed value. A fractal branching algorithm is then activated to extend lightning streamers away from the main channel and toward cloudy regions where substantial charge densities are present. Charges are neutralized along the tortuous lightning path with a simple procedure that preserves total charge conservation. The complete electrification scheme tested for an ideal case of vigorous supercellular storm shows an intense electrical activity all along its lifecycle. We show that the model is able to produce a direct tripolar structure of the charges as the result of a temperature charge reversal of - 10 °C and of the different sedimentation rates of the hydrometeors.

  18. Precipitation Processes Developed During ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999): Consistent 2D, Semi-3D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W-K.

    2003-01-01

    Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research (NACAR) and at NASA Goddard Space Flight Center . At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE, SCSMEX and KWAJEX using 512 by 512 km domain (with 2 km resolution). The results indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D GCE model simulations. The reason for the strong similarity between the 2D and 3D CRM simulations is that the same observed large-scale advective tendencies of potential temperature, water vapor mixing ratio, and horizontal momentum were used as the main focusing in both the 2D and 3D models. Interestingly, the 2D and 3D versions of the CRM used at CSU showed significant differences in the rainfall and cloud statistics for three ARM cases. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique, (2) calculate and examine the surface energy (especially radiation) and water budgets, and (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

  19. Precipitation Processes developed during ARM (1997), TOGA COARE(1992), GATE(1 974), SCSMEX(1998) and KWAJEX(1999): Consistent 2D and 3D Cloud Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.; Shie, C.-H.; Simpson, J.; Starr, D.; Johnson, D.; Sud, Y.

    2003-01-01

    Real clouds and clouds systems are inherently three dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud system with large horizontal domains at the National Center for Atmospheric Research. The results indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D simulations of these same cases. The reason for the strong similarity between the 2D and 3D CRM simulations is that the observed large-scale advective tendencies of potential temperature, water vapor mixing ratio, and horizontal momentum were used as the main forcing in both the 2D and 3D models. Interestingly, the 2D and 3D versions of the CRM used in CSU and U.K. Met Office showed significant differences in the rainfall and cloud statistics for three ARM cases. The major objectives of this project are to calculate and axamine: (1)the surface energy and water budgets, (2) the precipitation processes in the convective and stratiform regions, (3) the cloud upward and downward mass fluxes in the convective and stratiform regions; (4) cloud characteristics such as size, updraft intensity and lifetime, and (5) the entrainment and detrainment rates associated with clouds and cloud systems that developed in TOGA COARE, GATE, SCSMEX, ARM and KWAJEX. Of special note is that the analyzed (model generated) data sets are all produced by the same current version of the GCE model, i.e. consistent model physics and configurations. Trajectory analyse and inert tracer calculation will be conducted to identify the differences and similarities in the organization of convection between simulated 2D and 3D cloud systems.

  20. Simulated KWAJEX Convective Systems Using a 2D and 3D Cloud Resolving Model and Their Comparisons with Radar Observations

    NASA Technical Reports Server (NTRS)

    Shie, Chung-Lin; Tao, Wei-Kuo; Simpson, Joanne

    2003-01-01

    The 1999 Kwajalein Atoll field experiment (KWAJEX), one of several major TRMM (Tropical Rainfall Measuring Mission) field experiments, has successfully obtained a wealth of information and observation data on tropical convective systems over the western Central Pacific region. In this paper, clouds and convective systems that developed during three active periods (Aug 7-12, Aug 17-21, and Aug 29-Sep 13) around Kwajalein Atoll site are simulated using both 2D and 3D Goddard Cumulus Ensemble (GCE) models. Based on numerical results, the clouds and cloud systems are generally unorganized and short lived. These features are validated by radar observations that support the model results. Both the 2D and 3D simulated rainfall amounts and their stratiform contribution as well as the heat, water vapor, and moist static energy budgets are examined for the three convective episodes. Rainfall amounts are quantitatively similar between the two simulations, but the stratiform contribution is considerably larger in the 2D simulation. Regardless of dimension, fo all three cases, the large-scale forcing and net condensation are the two major physical processes that account for the evolution of the budgets with surface latent heat flux and net radiation solar and long-wave radiation)being secondary processes. Quantitative budget differences between 2D and 3D as well as between various episodes will be detailed.Morover, simulated radar signatures and Q1/Q2 fields from the three simulations are compared to each other and with radar and sounding observations.

  1. A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data

  2. A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data

  3. The Neighboring Column Approximation (NCA) - A fast approach for the calculation of 3D thermal heating rates in cloud resolving models

    NASA Astrophysics Data System (ADS)

    Klinger, Carolin; Mayer, Bernhard

    2016-01-01

    Due to computational costs, radiation is usually neglected or solved in plane parallel 1D approximation in today's numerical weather forecast and cloud resolving models. We present a fast and accurate method to calculate 3D heating and cooling rates in the thermal spectral range that can be used in cloud resolving models. The parameterization considers net fluxes across horizontal box boundaries in addition to the top and bottom boundaries. Since the largest heating and cooling rates occur inside the cloud, close to the cloud edge, the method needs in first approximation only the information if a grid box is at the edge of a cloud or not. Therefore, in order to calculate the heating or cooling rates of a specific grid box, only the directly neighboring columns are used. Our so-called Neighboring Column Approximation (NCA) is an analytical consideration of cloud side effects which can be considered a convolution of a 1D radiative transfer result with a kernel or radius of 1 grid-box (5 pt stencil) and which does usually not break the parallelization of a cloud resolving model. The NCA can be easily applied to any cloud resolving model that includes a 1D radiation scheme. Due to the neglect of horizontal transport of radiation further away than one model column, the NCA works best for model resolutions of about 100 m or lager. In this paper we describe the method and show a set of applications of LES cloud field snap shots. Correction terms, gains and restrictions of the NCA are described. Comprehensive comparisons to the 3D Monte Carlo Model MYSTIC and a 1D solution are shown. In realistic cloud fields, the full 3D simulation with MYSTIC shows cooling rates up to -150 K/d (100 m resolution) while the 1D solution shows maximum coolings of only -100 K/d. The NCA is capable of reproducing the larger 3D cooling rates. The spatial distribution of the heating and cooling is improved considerably. Computational costs are only a factor of 1.5-2 higher compared to a 1D

  4. Investigation of lightning flash morphologies along the entire supercell life cycle using a numerical 3D cloud resolving model(CRM).

    NASA Astrophysics Data System (ADS)

    Molinié, G.; Escobar, J.; Gazin, D.

    2008-12-01

    A stochastic lightning flash scheme has been implemented in line in a meso-sca le CRM. It is fully parallelized and vectorized. In this model, a lightning flash is schematized as two single conducting channels (single tracks) propagating in opposite directions from the lightning ignition point. Branch patterns propagate from the single channels. On the base of scale similarities between discharges in dielectrics at centimeter scales and lightning flashes, the stochastic scheme has been designed to compute branch trajec tories. Physical considerations and branch fractal dimensions compel branch trajectories. The charge neutralization operates along the single tracks and branches to threshold the cloud electrical charge. First, an assessment of the scheme will be presented in simple 2D configurations. Second, we will describe comprehensive 3D-thundercloud life-cycle simulations including cloud electrification and lightning discharges. Lightning flash patterns are analyzed through statistics of their effective fractal dimension. It is shown that paradoxically, lightning flashes with quasi-plane branch propagation (fractal dimension close to 2) lead to more steady electrical behavior than those completely filling volumes (fractal dimension close to 3).

  5. Cloud Resolving Modeling

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2007-01-01

    One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with cloud-resolving models (CRMs). CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (with sizes ranging from about 2-200 km). CRMs also allow for explicit interaction between clouds, outgoing longwave (cooling) and incoming solar (heating) radiation, and ocean and land surface processes. Observations are required to initialize CRMs and to validate their results. This paper provides a brief discussion and review of the main characteristics of CRMs as well as some of their major applications. These include the use of CRMs to improve our understanding of: (1) convective organization, (2) cloud temperature and water vapor budgets, and convective momentum transport, (3) diurnal variation of precipitation processes, (4) radiative-convective quasi-equilibrium states, (5) cloud-chemistry interaction, (6) aerosol-precipitation interaction, and (7) improving moist processes in large-scale models. In addition, current and future developments and applications of CRMs will be presented.

  6. Can 3D Point Clouds Replace GCPs?

    NASA Astrophysics Data System (ADS)

    Stavropoulou, G.; Tzovla, G.; Georgopoulos, A.

    2014-05-01

    Over the past decade, large-scale photogrammetric products have been extensively used for the geometric documentation of cultural heritage monuments, as they combine metric information with the qualities of an image document. Additionally, the rising technology of terrestrial laser scanning has enabled the easier and faster production of accurate digital surface models (DSM), which have in turn contributed to the documentation of heavily textured monuments. However, due to the required accuracy of control points, the photogrammetric methods are always applied in combination with surveying measurements and hence are dependent on them. Along this line of thought, this paper explores the possibility of limiting the surveying measurements and the field work necessary for the production of large-scale photogrammetric products and proposes an alternative method on the basis of which the necessary control points instead of being measured with surveying procedures are chosen from a dense and accurate point cloud. Using this point cloud also as a surface model, the only field work necessary is the scanning of the object and image acquisition, which need not be subject to strict planning. To evaluate the proposed method an algorithm and the complementary interface were produced that allow the parallel manipulation of 3D point clouds and images and through which single image procedures take place. The paper concludes by presenting the results of a case study in the ancient temple of Hephaestus in Athens and by providing a set of guidelines for implementing effectively the method.

  7. Effects of 1D and 3D Thermal Radiation on Cloud Dynamics and Microphysics

    NASA Astrophysics Data System (ADS)

    Klinger, C.; Mayer, B. C.; Jakub, F.; Zinner, T.

    2016-12-01

    Radiation is a key driver for the development of clouds. Solar radiation heats the surface and causes updrafts to rise, thus initializing cloud formation. In the very moment that a cloud forms, absorption and emission of thermal radiation at the cloud itself cause heating and cooling rates of several hundred K/d at the interface between cloud and cloudless sky. The magnitude of the cooling rates, compared to the commonly known clear sky cooling of 1-2 K/d, can alter cloud dynamics and microphysics and thus cloud development or lifetime. In cloud resolving numerical simulations, radiation is, if considered at all, usually applied as a 1D approximation, omitting horizontal transport of radiation through the modeling domain. However, it is obvious that radiation is a three dimensional problem. Applying 3D radiative transfer in cloud resolving simulations causes, in addition to cloud top cooling and cloud bottom warming, an additional cooling at cloud sides which is completely neglected by common 1D radiative transfer solutions. Here, we examine the effects of 1D and 3D thermal radiative transfer in cloud resolving simulation, by applying the newly developed "Neighboring Column Approximation" (NCA) - a fast 3D approximation for thermal radiative transfer in cloud resolving simulations. The NCA accurately represents 3D effects at moderate computational cost which make it an ideal tool to explore how 1D and 3D radiative transfer modify cloud development in numerical models. Thermal radiation can modify clouds in terms of cloud lifetime, cloud size and cloud circulation. These effects on cloud development will be analyzed in a set of cumulus cloud simulations.

  8. Extensible 3D (X3D) Graphics Clouds for Geographic Information Systems

    DTIC Science & Technology

    2008-03-01

    browser such as Microsoft Internet Explorer or Netscape using an X3D or VRML supporting plug-in. The benefits of diverse support can cause...typing model output with a particular method of 3D cloud production. Data-driven adaptation and production of cloud models for web -based delivery...and production of cloud models for web -based delivery is an achievable capability given continued research and development. vi THIS PAGE

  9. Alignment of continuous video onto 3D point clouds.

    PubMed

    Zhao, Wenyi; Nister, David; Hsu, Steve

    2005-08-01

    We propose a general framework for aligning continuous (oblique) video onto 3D sensor data. We align a point cloud computed from the video onto the point cloud directly obtained from a 3D sensor. This is in contrast to existing techniques where the 2D images are aligned to a 3D model derived from the 3D sensor data. Using point clouds enables the alignment for scenes full of objects that are difficult to model; for example, trees. To compute 3D point clouds from video, motion stereo is used along with a state-of-the-art algorithm for camera pose estimation. Our experiments with real data demonstrate the advantages of the proposed registration algorithm for texturing models in large-scale semiurban environments. The capability to align video before a 3D model is built from the 3D sensor data offers new practical opportunities for 3D modeling. We introduce a novel modeling-through-registration approach that fuses 3D information from both the 3D sensor and the video. Initial experiments with real data illustrate the potential of the proposed approach.

  10. 3D reconstruction of tropospheric cirrus clouds

    NASA Astrophysics Data System (ADS)

    Kouahla, M. N.; Faivre, M.; Moreels, G.; Seridi, H.

    2016-10-01

    In this paper, we present a series of results from stereo-imagery of cirrus clouds in the troposphere. These clouds are either of natural origin or are created by aircraft exhausts. They are presently considered to be a major cause for the climate change. Two observation campaigns were conducted in France in 2013 and 2014. The observing sites were located in Marnay (47°17‧31.5″ N, 5°44‧58.8″ E; altitude 275 m) and in Mont Poupet (46°58‧31.5″ N, 5°52‧22.7″ E; altitude 600 m). The distance between both sites was 36 km. We used numeric CMOS photographic cameras. The image processing sequence included a contrast enhancement and a perspective inversion to obtain a satellite-type view. Finally, the triangulation procedure was used in an area that is a common part of both fields of view.

  11. Automatic 3-D Point Cloud Classification of Urban Environments

    DTIC Science & Technology

    2008-12-01

    paper, we address the problem of automated interpretation of 3-D point clouds from scenes of urban and natural environments; our analysis is...over 10 km of traverse. We implemented three geometric features com- monly used in spectral analysis of point clouds . We de- fine λ2 ≥ λ1 ≥ λ0 to be

  12. 3D scene reconstruction based on 3D laser point cloud combining UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Huiyun; Yan, Yangyang; Zhang, Xitong; Wu, Zhenzhen

    2016-03-01

    It is a big challenge capturing and modeling 3D information of the built environment. A number of techniques and technologies are now in use. These include GPS, and photogrammetric application and also remote sensing applications. The experiment uses multi-source data fusion technology for 3D scene reconstruction based on the principle of 3D laser scanning technology, which uses the laser point cloud data as the basis and Digital Ortho-photo Map as an auxiliary, uses 3DsMAX software as a basic tool for building three-dimensional scene reconstruction. The article includes data acquisition, data preprocessing, 3D scene construction. The results show that the 3D scene has better truthfulness, and the accuracy of the scene meet the need of 3D scene construction.

  13. SACR ADVance 3-D Cartesian Cloud Cover (SACR-ADV-3D3C) product

    DOE Data Explorer

    Meng Wang, Tami Toto, Eugene Clothiaux, Katia Lamer, Mariko Oue

    2017-03-08

    SACR-ADV-3D3C remaps the outputs of SACRCORR for cross-wind range-height indicator (CW-RHI) scans to a Cartesian grid and reports reflectivity CFAD and best estimate domain averaged cloud fraction. The final output is a single NetCDF file containing all aforementioned corrected radar moments remapped on a 3-D Cartesian grid, the SACR reflectivity CFAD, a profile of best estimate cloud fraction, a profile of maximum observable x-domain size (xmax), a profile time to horizontal distance estimate and a profile of minimum observable reflectivity (dBZmin).

  14. Point Cloud Visualization in AN Open Source 3d Globe

    NASA Astrophysics Data System (ADS)

    De La Calle, M.; Gómez-Deck, D.; Koehler, O.; Pulido, F.

    2011-09-01

    During the last years the usage of 3D applications in GIS is becoming more popular. Since the appearance of Google Earth, users are familiarized with 3D environments. On the other hand, nowadays computers with 3D acceleration are common, broadband access is widespread and the public information that can be used in GIS clients that are able to use data from the Internet is constantly increasing. There are currently several libraries suitable for this kind of applications. Based on these facts, and using libraries that are already developed and connected to our own developments, we are working on the implementation of a real 3D GIS with analysis capabilities. Since a 3D GIS such as this can be very interesting for tasks like LiDAR or Laser Scanner point clouds rendering and analysis, special attention is given to get an optimal handling of very large data sets. Glob3 will be a multidimensional GIS in which 3D point clouds could be explored and analysed, even if they are consist of several million points.The latest addition to our visualization libraries is the development of a points cloud server that works regardless of the cloud's size. The server receives and processes petitions from a 3d client (for example glob3, but could be any other, such as one based on WebGL) and delivers the data in the form of pre-processed tiles, depending on the required level of detail.

  15. Global impact of 3D cloud-radiation interactions

    NASA Astrophysics Data System (ADS)

    Schäfer, Sophia; Hogan, Robin; Fielding, Mark; Chiu, Christine

    2017-04-01

    Clouds have a decisive impact on the Earth's radiation budget and on the temperature of the atmosphere and surface. However, in global weather and climate models, cloud-radiation interaction is treated in only the vertical dimension using several non-realistic assumptions, which contributes to the large uncertainty on the climatic role of clouds. We provide a first systematic investigation into the impact of horizontal radiative transport for both shortwave and longwave radiation on a global, long-term scale. For this purpose, we have developed and validated the SPARTACUS radiation scheme, a method for including three-dimensional radiative transfer effects approximately in a one-dimensional radiation calculation that is numerically efficient enough for global calculations, allowing us to conduct 1D and quasi-3D radiation calculations for a year of global of ERA-Interim re-analysis atmospheric data and compare the results of various radiation treatments. SPARTACUS includes the effects of cloud internal inhomogeneity, horizontal in-region transport and the spatial distribution of in-cloud radiative fluxes.The impact of varying three-dimensional cloud geometry can be described by one parameter, the effective cloud scale, which has a characteristic value for each cloud type. We find that both the 3D effects of cloud-side transport and of horizontal in-cloud radiative transport in the shortwave are significant. Overall, 3D cloud effects warm the Earth by about 4 W m -2 , with warming effects in both the shortwave and the longwave. The dominant 3D cloud effect is the previously rarely investigated in-region horizontal transfer effect in the shortwave, which significantly decreases cloud reflectance and warms the Earth system by 5 W m -2 , partly counteracted by the cooling effect of shortwave 3D cloud-side transport. Longwave heating and cooling at various heights is strengthened by up to 0.2 K d ^{-1} and -0.3 K d ^{-1} respectively. These 3D effects, neglected by

  16. 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.

  17. 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.

  18. 3D Building Reconstruction Using Dense Photogrammetric Point Cloud

    NASA Astrophysics Data System (ADS)

    Malihi, S.; Valadan Zoej, M. J.; Hahn, M.; Mokhtarzade, M.; Arefi, H.

    2016-06-01

    Three dimensional models of urban areas play an important role in city planning, disaster management, city navigation and other applications. Reconstruction of 3D building models is still a challenging issue in 3D city modelling. Point clouds generated from multi view images of UAV is a novel source of spatial data, which is used in this research for building reconstruction. The process starts with the segmentation of point clouds of roofs and walls into planar groups. By generating related surfaces and using geometrical constraints plus considering symmetry, a 3d model of building is reconstructed. In a refinement step, dormers are extracted, and their models are reconstructed. The details of the 3d reconstructed model are in LoD3 level, with respect to modelling eaves, fractions of roof and dormers.

  19. Uniform grid upsampling of 3D lidar point cloud data

    NASA Astrophysics Data System (ADS)

    Gurram, Prudhvi; Hu, Shuowen; Chan, Alex

    2013-03-01

    Airborne laser scanning light detection and ranging (LiDAR) systems are used for remote sensing topology and bathymetry. The most common data collection technique used in LiDAR systems employs a linear mode scanning. The resulting scanning data form a non-uniformly sampled 3D point cloud. To interpret and further process the 3D point cloud data, these raw data are usually converted to digital elevation models (DEMs). In order to obtain DEMs in a uniform and upsampled raster format, the elevation information from the available non-uniform 3D point cloud data are mapped onto the uniform grid points. After the mapping is done, the grid points with missing elevation information are lled by using interpolation techniques. In this paper, partial di erential equations (PDE) based approach is proposed to perform the interpolation and to upsample the 3D point cloud onto a uniform grid. Due to the desirable e ects of using higher order PDEs, smoothness is maintained over homogeneous regions, while sharp edge information in the scene well preserved. The proposed algorithm reduces the draping e ects near the edges of distinctive objects in the scene. Such annoying draping e ects are commonly associated with existing point cloud rendering algorithms. Simulation results are presented in this paper to illustrate the advantages of the proposed algorithm.

  20. Cloud Based Web 3d GIS Taiwan Platform

    NASA Astrophysics Data System (ADS)

    Tsai, W.-F.; Chang, J.-Y.; Yan, S. Y.; Chen, B.

    2011-09-01

    This article presents the status of the web 3D GIS platform, which has been developed in the National Applied Research Laboratories. The purpose is to develop a global earth observation 3D GIS platform for applications to disaster monitoring and assessment in Taiwan. For quick response to preliminary and detailed assessment after a natural disaster occurs, the web 3D GIS platform is useful to access, transfer, integrate, display and analyze the multi-scale huge data following the international OGC standard. The framework of cloud service for data warehousing management and efficiency enhancement using VMWare is illustrated in this article.

  1. 2D-3D transition of gold cluster anions resolved

    NASA Astrophysics Data System (ADS)

    Johansson, Mikael P.; Lechtken, Anne; Schooss, Detlef; Kappes, Manfred M.; Furche, Filipp

    2008-05-01

    Small gold cluster anions Aun- are known for their unusual two-dimensional (2D) structures, giving rise to properties very different from those of bulk gold. Previous experiments and calculations disagree about the number of gold atoms nc where the transition to 3D structures occurs. We combine trapped ion electron diffraction and state of the art electronic structure calculations to resolve this puzzle and establish nc=12 . It is shown that theoretical studies using traditional generalized gradient functionals are heavily biased towards 2D structures. For a correct prediction of the 2D-3D crossover point it is crucial to use density functionals yielding accurate jellium surface energies, such as the Tao-Perdew-Staroverov-Scuseria (TPSS) functional or the Perdew-Burke-Ernzerhof functional modified for solids (PBEsol). Further, spin-orbit effects have to be included, and large, flexible basis sets employed. This combined theoretical-experimental approach is promising for larger gold and other metal clusters.

  2. Mirror Identification and Correction of 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Käshammer, P.-F.; Nüchter, A.

    2015-02-01

    In terrestrial laser scanning (TLS), the surface geometry of objects is scanned by laser beams and recorded digitally. This produces a discrete set of scan points, commonly referred to as a point cloud. The coordinates of the scan points are determined by measuring the angles and the time-of-flight relative to the origin (scanner position). However, if it comes to mirror surfaces laser beams are fully reflected, due to the high reflectivity. Mirrors do not appear in the point cloud at all. Instead, for every reflected beam, a incorrect scan point is created behind the actual mirror plane. Consequently, problems arise in multiple derived application fields such as 3D virtual reconstruction of complex architectures. The paper presents a new approach to automatically detect framed rectangular mirrors with known dimensions and to correct the 3D point cloud, using the calculated mirror plane.

  3. Disocclusion of 3d LIDAR Point Clouds Using Range Images

    NASA Astrophysics Data System (ADS)

    Biasutti, P.; Aujol, J.-F.; Brédif, M.; Bugeau, A.

    2017-05-01

    This paper proposes a novel framework for the disocclusion of mobile objects in 3D LiDAR scenes aquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle this problem directly in the 3D space. This work promotes an alternative approach by using a 2D range image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. First, the point cloud is turned into a 2D range image by exploiting the sensor's topology. Using the range image, a semi-automatic segmentation procedure based on depth histograms is performed in order to select the occluding object to be removed. A variational image inpainting technique is then used to reconstruct the area occluded by that object. Finally, the range image is unprojected as a 3D point cloud. Experiments on real data prove the effectiveness of this procedure both in terms of accuracy and speed.

  4. Parameterization of Solar Radiative Fluxes For 3d-inhomogeneous Clouds

    NASA Astrophysics Data System (ADS)

    Schewski, M.; Macke, A.

    radiative fluxes for 3d clouds appears to be a promis- ing approach.

  5. Reconstruction of 3-D cloud geometry using a scanning cloud radar

    NASA Astrophysics Data System (ADS)

    Ewald, F.; Winkler, C.; Zinner, T.

    2014-11-01

    Clouds are one of the main reasons of uncertainties in the forecasts of weather and climate. In part, this is due to limitations of remote sensing of cloud microphysics. Present approaches often use passive spectral measurements for the remote sensing of cloud microphysical parameters. Large uncertainties are introduced by three dimensional (3-D) radiative transfer effects and cloud inhomogeneities. Such effects are largely caused by unknown orientation of cloud sides or by shadowed areas on the cloud. Passive ground based remote sensing of cloud properties at high spatial resolution could be improved crucially with this kind of additional knowledge of cloud geometry. To this end, a method for the accurate reconstruction of 3-D cloud geometry from cloud radar measurements is developed in this work. Using a radar simulator and simulated passive measurements of static LES model clouds, the effects of different radar scan resolutions and varying interpolation methods are evaluated. In reality a trade-off between scan resolution and scan duration has to be found as clouds are changing quickly. A reasonable choice is a scan resolution of 1 to 2°. The most suitable interpolation procedure identified is the barycentric interpolation method. The 3-D reconstruction method is demonstrated using radar scans of convective cloud cases with the Munich miraMACS, a 35 GHz scanning cloud radar. As a successful proof of concept, camera imagery collected at the radar location is reproduced for the observed cloud cases via 3-D volume reconstruction and 3-D radiative transfer simulation. Data sets provided by the presented reconstruction method will aid passive spectral ground-based measurements of cloud sides to retrieve microphysical parameters.

  6. Extraction of features from 3D laser scanner cloud data

    NASA Astrophysics Data System (ADS)

    Chan, Vincent H.; Bradley, Colin H.; Vickers, Geoffrey W.

    1997-12-01

    One of the road blocks on the path of automated reverse engineering has been the extraction of useful data from the copious range data generated from 3-D laser scanning systems. A method to extract the relevant features of a scanned object is presented. A 3-D laser scanner is automatically directed to obtain discrete laser cloud data on each separate patch that constitutes the object's surface. With each set of cloud data treated as a separate entity, primitives are fitted to the data resulting in a geometric and topologic database. Using a feed-forewarn neural network, the data is analyzed for geometric combinations that make up machine features such as through holes and slots. These features are required for the reconstruction of the solid model by a machinist or feature based CAM algorithms, thus completing the reverse engineering cycle.

  7. 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.

  8. 3D matching techniques using OCT fingerprint point clouds

    NASA Astrophysics Data System (ADS)

    Gutierrez da Costa, Henrique S.; Silva, Luciano; Bellon, Olga R. P.; Bowden, Audrey K.; Czovny, Raphael K.

    2017-02-01

    Optical Coherence Tomography (OCT) makes viable acquisition of 3D fingerprints from both dermis and epidermis skin layers and their interfaces, exposing features that can be explored to improve biometric identification such as the curvatures and distinctive 3D regions. Scanned images from eleven volunteers allowed the construction of the first OCT 3D fingerprint database, to our knowledge, containing epidermal and dermal fingerprints. 3D dermal fingerprints can be used to overcome cases of Failure to Enroll (FTE) due to poor ridge image quality and skin alterations, cases that affect 2D matching performance. We evaluate three matching techniques, including the well-established Iterative Closest Points algorithm (ICP), Surface Interpenetration Measure (SIM) and the well-known KH Curvature Maps, all assessed using a 3D OCT fingerprint database, the first one for this purpose. Two of these techniques are based on registration techniques and one on curvatures. These were evaluated, compared and the fusion of matching scores assessed. We applied a sequence of steps to extract regions of interest named (ROI) minutiae clouds, representing small regions around distinctive minutia, usually located at ridges/valleys endings or bifurcations. The obtained ROI is acquired from the epidermis and dermis-epidermis interface by OCT imaging. A comparative analysis of identification accuracy was explored using different scenarios and the obtained results shows improvements for biometric identification. A comparison against 2D fingerprint matching algorithms is also presented to assess the improvements.

  9. Underwater 3d Modeling: Image Enhancement and Point Cloud Filtering

    NASA Astrophysics Data System (ADS)

    Sarakinou, I.; Papadimitriou, K.; Georgoula, O.; Patias, P.

    2016-06-01

    This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images' radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

  10. 3D reconstruction of tropospheric cirrus clouds by stereovision system

    NASA Astrophysics Data System (ADS)

    Nadjib Kouahla, Mohamed; Moreels, Guy; Seridi, Hamid

    2016-07-01

    A stereo imaging method is applied to measure the altitude of cirrus clouds and provide a 3D map of the altitude of the layer centroid. They are located in the high troposphere and, sometimes in the lower stratosphere, between 6 and 10 km high. Two simultaneous images of the same scene are taken with Canon cameras (400D) in two sites distant of 37 Km. Each image processed in order to invert the perspective effect and provide a satellite-type view of the layer. Pairs of matched points that correspond to a physical emissive point in the common area are identified in calculating a correlation coefficient (ZNCC: Zero mean Normalized Cross-correlation or ZSSD: as Zero mean Sum of Squared Differences). This method is suitable for obtaining 3D representations in the case of low-contrast objects. An observational campaign was conducted in June 2014 in France. The images were taken simultaneously at Marnay (47°17'31.5" N, 5°44'58.8" E; altitude 275 m) 25 km northwest of Besancon and in Mont poupet (46°58'31.5" N, 5°52'22.7" E; altitude 600 m) southwest of Besancon at 43 km. 3D maps of the Natural cirrus clouds and artificial like "aircraft trails" are retrieved. They are compared with pseudo-relief intensity maps of the same region. The mean altitude of the cirrus barycenter is located at 8.5 ± 1km on June 11.

  11. 3-D Object Recognition from Point Cloud Data

    NASA Astrophysics Data System (ADS)

    Smith, W.; Walker, A. S.; Zhang, B.

    2011-09-01

    The market for real-time 3-D mapping includes not only traditional geospatial applications but also navigation of unmanned autonomous vehicles (UAVs). Massively parallel processes such as graphics processing unit (GPU) computing make real-time 3-D object recognition and mapping achievable. Geospatial technologies such as digital photogrammetry and GIS offer advanced capabilities to produce 2-D and 3-D static maps using UAV data. The goal is to develop real-time UAV navigation through increased automation. It is challenging for a computer to identify a 3-D object such as a car, a tree or a house, yet automatic 3-D object recognition is essential to increasing the productivity of geospatial data such as 3-D city site models. In the past three decades, researchers have used radiometric properties to identify objects in digital imagery with limited success, because these properties vary considerably from image to image. Consequently, our team has developed software that recognizes certain types of 3-D objects within 3-D point clouds. Although our software is developed for modeling, simulation and visualization, it has the potential to be valuable in robotics and UAV applications. The locations and shapes of 3-D objects such as buildings and trees are easily recognizable by a human from a brief glance at a representation of a point cloud such as terrain-shaded relief. The algorithms to extract these objects have been developed and require only the point cloud and minimal human inputs such as a set of limits on building size and a request to turn on a squaring option. The algorithms use both digital surface model (DSM) and digital elevation model (DEM), so software has also been developed to derive the latter from the former. The process continues through the following steps: identify and group 3-D object points into regions; separate buildings and houses from trees; trace region boundaries; regularize and simplify boundary polygons; construct complex roofs. Several case

  12. A 3D Cloud-Construction Algorithm for the EarthCARE Satellite Mission

    NASA Technical Reports Server (NTRS)

    Barker, H. W.; Jerg, M. P.; Wehr, T.; Kato, S.; Donovan, D. P.; Hogan, R. J.

    2011-01-01

    This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data.

  13. A 3D Cloud-Construction Algorithm for the EarthCARE Satellite Mission

    NASA Technical Reports Server (NTRS)

    Barker, H. W.; Jerg, M. P.; Wehr, T.; Kato, S.; Donovan, D. P.; Hogan, R. J.

    2011-01-01

    This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data.

  14. The medial scaffold of 3D unorganized point clouds.

    PubMed

    Leymarie, Frederic F; Kimia, Benjamin B

    2007-02-01

    We introduce the notion of the medial scaffold, a hierarchical organization of the medial axis of a 3D shape in the form of a graph constructed from special medial curves connecting special medial points. A key advantage of the scaffold is that it captures the qualitative aspects of shape in a hierarchical and tightly condensed representation. We propose an efficient and exact method for computing the medial scaffold based on a notion of propagation along the scaffold itself, starting from initial sources of the flow and constructing the scaffold during the propagation. We examine this method specifically in the context of an unorganized cloud of points in 3D, e.g., as obtained from laser range finders, which typically involve hundreds of thousands of points, but the ideas are generalizable to data arising from geometrically described surface patches. The computational bottleneck in the propagation-based scheme is in finding the initial sources of the flow. We thus present several ideas to avoid the unnecessary consideration of pairs of points which cannot possibly form a medial point source, such as the "visibility" of a point from another given a third point and the interaction of clusters of points. An application of using the medial scaffold for the representation of point samplings of real-life objects is also illustrated.

  15. Scanning Cloud Radar Observations at Azores: Preliminary 3D Cloud Products

    SciTech Connect

    Kollias, P.; Johnson, K.; Jo, I.; Tatarevic, A.; Giangrande, S.; Widener, K.; Bharadwaj, N.; Mead, J.

    2010-03-15

    The deployment of the Scanning W-Band ARM Cloud Radar (SWACR) during the AMF campaign at Azores signals the first deployment of an ARM Facility-owned scanning cloud radar and offers a prelude for the type of 3D cloud observations that ARM will have the capability to provide at all the ARM Climate Research Facility sites by the end of 2010. The primary objective of the deployment of Scanning ARM Cloud Radars (SACRs) at the ARM Facility sites is to map continuously (operationally) the 3D structure of clouds and shallow precipitation and to provide 3D microphysical and dynamical retrievals for cloud life cycle and cloud-scale process studies. This is a challenging task, never attempted before, and requires significant research and development efforts in order to understand the radar's capabilities and limitations. At the same time, we need to look beyond the radar meteorology aspects of the challenge and ensure that the hardware and software capabilities of the new systems are utilized for the development of 3D data products that address the scientific needs of the new Atmospheric System Research (ASR) program. The SWACR observations at Azores provide a first look at such observations and the challenges associated with their analysis and interpretation. The set of scan strategies applied during the SWACR deployment and their merit is discussed. The scan strategies were adjusted for the detection of marine stratocumulus and shallow cumulus that were frequently observed at the Azores deployment. Quality control procedures for the radar reflectivity and Doppler products are presented. Finally, preliminary 3D-Active Remote Sensing of Cloud Locations (3D-ARSCL) products on a regular grid will be presented, and the challenges associated with their development discussed. In addition to data from the Azores deployment, limited data from the follow-up deployment of the SWACR at the ARM SGP site will be presented. This effort provides a blueprint for the effort required for the

  16. 3D resolved mapping of optical aberrations in thick tissues

    PubMed Central

    Zeng, Jun; Mahou, Pierre; Schanne-Klein, Marie-Claire; Beaurepaire, Emmanuel; Débarre, Delphine

    2012-01-01

    We demonstrate a simple method for mapping optical aberrations with 3D resolution within thick samples. The method relies on the local measurement of the variation in image quality with externally applied aberrations. We discuss the accuracy of the method as a function of the signal strength and of the aberration amplitude and we derive the achievable resolution for the resulting measurements. We then report on measured 3D aberration maps in human skin biopsies and mouse brain slices. From these data, we analyse the consequences of tissue structure and refractive index distribution on aberrations and imaging depth in normal and cleared tissue samples. The aberration maps allow the estimation of the typical aplanetism region size over which aberrations can be uniformly corrected. This method and data pave the way towards efficient correction strategies for tissue imaging applications. PMID:22876353

  17. Desktop Cloud Visualization: the new technology to remote access 3D interactive applications in the Cloud.

    PubMed

    Torterolo, Livia; Ruffino, Francesco

    2012-01-01

    In the proposed demonstration we will present DCV (Desktop Cloud Visualization): a unique technology that allows users to remote access 2D and 3D interactive applications over a standard network. This allows geographically dispersed doctors work collaboratively and to acquire anatomical or pathological images and visualize them for further investigations.

  18. Cloud4Psi: cloud computing for 3D protein structure similarity searching.

    PubMed

    Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Kłapciński, Artur

    2014-10-01

    Popular methods for 3D protein structure similarity searching, especially those that generate high-quality alignments such as Combinatorial Extension (CE) and Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) are still time consuming. As a consequence, performing similarity searching against large repositories of structural data requires increased computational resources that are not always available. Cloud computing provides huge amounts of computational power that can be provisioned on a pay-as-you-go basis. We have developed the cloud-based system that allows scaling of the similarity searching process vertically and horizontally. Cloud4Psi (Cloud for Protein Similarity) was tested in the Microsoft Azure cloud environment and provided good, almost linearly proportional acceleration when scaled out onto many computational units. Cloud4Psi is available as Software as a Service for testing purposes at: http://cloud4psi.cloudapp.net/. For source code and software availability, please visit the Cloud4Psi project home page at http://zti.polsl.pl/dmrozek/science/cloud4psi.htm. © The Author 2014. Published by Oxford University Press.

  19. Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data

    NASA Technical Reports Server (NTRS)

    Zeng, Xiping; Tao, Wei-Kuo; Zhang, Minghua; Peters-Lidard, Christa; Lang, Stephen; Simpson, Joanne; Kumar, Sujay; Xie, Shaocheng; Eastman, Joseph L.; Shie, Chung-Lin; Geiger, James V.

    2006-01-01

    Two 20-day, continental midlatitude cases are simulated with a three-dimensional (3D) cloud-resolving model (CRM) and compared to Atmospheric Radiation Measurement (ARM) data. This evaluation of long-term cloud-resolving model simulations focuses on the evaluation of clouds and surface fluxes. All numerical experiments, as compared to observations, simulate surface precipitation well but over-predict clouds, especially in the upper troposphere. The sensitivity of cloud properties to dimensionality and other factors is studied to isolate the origins of the over prediction of clouds. Due to the difference in buoyancy damping between 2D and 3D models, surface precipitation fluctuates rapidly with time, and spurious dehumidification occurs near the tropopause in the 2D CRM. Surface fluxes from a land data assimilation system are compared with ARM observations. They are used in place of the ARM surface fluxes to test the sensitivity of simulated clouds to surface fluxes. Summertime simulations show that surface fluxes from the assimilation system bring about a better simulation of diurnal cloud variation in the lower troposphere.

  20. Do Fractal Models of Clouds Produces the Right 3D Radiative Effects?

    NASA Technical Reports Server (NTRS)

    Varnai, Tamas; Marshak, Alexander; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Stochastic fractal models of clouds are often used to study 3D radiative effects and their influence on the remote sensing of cloud properties. Since it is important that the cloud models produce a correct radiative response, some researchers require the model parameters to match observed cloud properties such as scale-independent optical thickness variability. Unfortunately, matching these properties does not necessarily imply that the cloud models will cause the right 3D radiative effects. First, the matched properties alone only influence the 3D effects but do not completely determine them. Second, in many cases the retrieved cloud properties have been already biased by 3D radiative effects, and so the models may not match the true real clouds. Finally, the matched cloud properties cannot be considered independent from the scales at which they have been retrieved. This paper proposes an approach that helps ensure that fractal cloud models are realistic and produce the right 3D effects. The technique compares the results of radiative transfer simulations for the model clouds to new direct observations of 3D radiative effects in satellite images.

  1. Parameterization and analysis of 3-D radiative transfer in clouds

    SciTech Connect

    Varnai, Tamas

    2012-03-16

    This report provides a summary of major accomplishments from the project. The project examines the impact of radiative interactions between neighboring atmospheric columns, for example clouds scattering extra sunlight toward nearby clear areas. While most current cloud models don't consider these interactions and instead treat sunlight in each atmospheric column separately, the resulting uncertainties have remained unknown. This project has provided the first estimates on the way average solar heating is affected by interactions between nearby columns. These estimates have been obtained by combining several years of cloud observations at three DOE Atmospheric Radiation Measurement (ARM) Climate Research Facility sites (in Alaska, Oklahoma, and Papua New Guinea) with simulations of solar radiation around the observed clouds. The importance of radiative interactions between atmospheric columns was evaluated by contrasting simulations that included the interactions with those that did not. This study provides lower-bound estimates for radiative interactions: It cannot consider interactions in cross-wind direction, because it uses two-dimensional vertical cross-sections through clouds that were observed by instruments looking straight up as clouds drifted aloft. Data from new DOE scanning radars will allow future radiative studies to consider the full three-dimensional nature of radiative processes. The results reveal that two-dimensional radiative interactions increase overall day-and-night average solar heating by about 0.3, 1.2, and 4.1 Watts per meter square at the three sites, respectively. This increase grows further if one considers that most large-domain cloud simulations have resolutions that cannot specify small-scale cloud variability. For example, the increases in solar heating mentioned above roughly double for a fairly typical model resolution of 1 km. The study also examined the factors that shape radiative interactions between atmospheric columns and

  2. Taking a 3-D Slice of Hurricane Maria's Cloud Structure

    NASA Image and Video Library

    2017-09-20

    NASA's CloudSat satellite flew over Hurricane Maria on Sept. 17, 2017, at 1:23 p.m. EDT (17:23 UTC) as the storm had just strengthened into a hurricane in the Atlantic Ocean. Hurricane Maria contained estimated maximum sustained winds of 75 miles per hour (65 knots) and had a minimum barometric pressure of 986 millibars. CloudSat flew over Maria through the center of the rapidly intensifying storm, directly through an overshooting cloud top (a dome-shaped protrusion that shoots out of the top of the anvil cloud of a thunderstorm). CloudSat reveals the vertical extent of the overshooting cloud top, showing the estimated height of the cloud to be 11 miles (18 kilometers). Areas of high reflectivity with deep red and pink colors extend well above 9 miles (15 kilometers) in height, showing large amounts of water being drawn upward high into the atmosphere. A movie is available at https://photojournal.jpl.nasa.gov/catalog/PIA21961

  3. 3D Scanning Cloud Radar Observations at Azores during the ARM AMF field campaign: Reconstruction and study of 3D cloud structures and properties

    NASA Astrophysics Data System (ADS)

    Bowley, K.; Jo, I.; Tatarevic, A.; Kollias, P.

    2010-12-01

    The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) has been operating at Graciosa Island (Azores) since May 2009. This 21-month field campaign focuses on the study of marine stratus clouds. The ARM/AMF instrumentation and location provides a unique opportunity to observe the cloud properties of marine stratocumulus utilizing a variety of active and passive remote sensors. In addition to the standard profiling instrumentation, the first scanning W-band (94-GHz) ARM Cloud Radar (SWACR) was deployed for a short two-month period (October-November 2009). Several scan strategies were tested during the SWACR deployment. The scan strategies were designed specifically to provide the ability to reconstruct the 3D cloud structure. The raw radar observations are quality controlled with the identification of radar volumes with significant detections, water vapor attenuation and unfolding of the radar Doppler velocity. The observations are also transformed from the original radar coordinate system (spherical) to a Cartesian coordinate system using an adaptive gridding algorithm. The 3D gridding of the radar observables, along with spatial data analysis, allow us to evaluate important issues, specifically spatial variability of cloud and drizzle structures. Column profiles of SWACR observables are used in combination with Liquid Water Path measurements from the collocated Microwave Radiometer (MWR) to develop new relationships to compute Liquid Water Content (LWC). The best possible estimate of the 3D LWC structure is reconstructed by assessing both our relationship and other known relationships between radar reflectivity and LWC. This is required in order to use the 3D cloud observations for radiative transfer modeling. Additional drizzle-identification techniques are also being developed to allow the isolation of 3D cloud-only or liquid-only fields. These types of variables have a key impact on the understanding of the radiative budget

  4. 3D modeling of clouds in GJ1214b's atmosphere

    NASA Astrophysics Data System (ADS)

    Charnay, Benjamin; Meadows, Victoria; leconte, Jérémy; Misra, Amit; Arnay, Giada

    2015-12-01

    GJ1214b is a warm mini-Neptune/waterworld and one of the few low-mass exoplanets whose atmosphere is characterizable by current telescopes. Recent observations indicated a flat transit spectrum in near-infrared which has been interpreted as the presence of high and thick condensate clouds of KCl or ZnS or photochemical hazes [1]. However, the formation of such high clouds/hazes would require a strong vertical mixing linked to the atmospheric circulation [2]. In order to understand the transport, distribution and observational implications of such clouds/haze, we studied the atmospheric circulation and cloud formation on GJ1214b for H-dominated and water-dominated atmospheres using the Generic LMDZ GCM.Firstly, we analyzed cloud-free atmospheres [3]. We showed that the zonal mean meridional circulation corresponds to an anti-Hadley circulation in most of the atmosphere with upwelling at midlatitude and downwelling at the equator. This circulation should strongly impact cloud formation and distribution, leading to a minimum of cloud at the equator. We also derived 1D equivalent eddy diffusion coefficients. The corresponding values should favor an efficient formation of photochemical haze in the upper atmosphere of GJ1214b.Secondly, we simulated cloudy atmospheres including latent heat release and radiative effects for KCl and ZnS clouds [4]. We analyzed their distribution and their impacts on the thermal structure. In particular, a stratospheric thermal inversion should likely be formed by absorption of stellar radiation by ZnS clouds. We showed that flat transit spectra consistent with HST observations are possible for cloud particle radii around 0.5 microns. Using the outputs of our GCM, we also generated emission and reflection spectra and phases curves.Finally, our results suggest that primary and secondary eclipses and phase curves observed by JWST should provide strong constraints on the nature of GJ1214b's atmosphere and clouds.references:[1] Kreidberg et al

  5. Overlap Properties of Clouds Generated by a Cloud Resolving Model

    NASA Technical Reports Server (NTRS)

    Oreopoulos, L.; Khairoutdinov, M.

    2002-01-01

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

  6. Extension of RCC Topological Relations for 3d Complex Objects Components Extracted from 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Xing, Xu-Feng; Abolfazl Mostafavia, Mir; Wang, Chen

    2016-06-01

    Topological relations are fundamental for qualitative description, querying and analysis of a 3D scene. Although topological relations for 2D objects have been extensively studied and implemented in GIS applications, their direct extension to 3D is very challenging and they cannot be directly applied to represent relations between components of complex 3D objects represented by 3D B-Rep models in R3. Herein we present an extended Region Connection Calculus (RCC) model to express and formalize topological relations between planar regions for creating 3D model represented by Boundary Representation model in R3. We proposed a new dimension extended 9-Intersection model to represent the basic relations among components of a complex object, including disjoint, meet and intersect. The last element in 3*3 matrix records the details of connection through the common parts of two regions and the intersecting line of two planes. Additionally, this model can deal with the case of planar regions with holes. Finally, the geometric information is transformed into a list of strings consisting of topological relations between two planar regions and detailed connection information. The experiments show that the proposed approach helps to identify topological relations of planar segments of point cloud automatically.

  7. From Tls Point Clouds to 3d Models of Trees: a Comparison of Existing Algorithms for 3d Tree Reconstruction

    NASA Astrophysics Data System (ADS)

    Bournez, E.; Landes, T.; Saudreau, M.; Kastendeuch, P.; Najjar, G.

    2017-02-01

    3D models of tree geometry are important for numerous studies, such as for urban planning or agricultural studies. In climatology, tree models can be necessary for simulating the cooling effect of trees by estimating their evapotranspiration. The literature shows that the more accurate the 3D structure of a tree is, the more accurate microclimate models are. This is the reason why, since 2013, we have been developing an algorithm for the reconstruction of trees from terrestrial laser scanner (TLS) data, which we call TreeArchitecture. Meanwhile, new promising algorithms dedicated to tree reconstruction have emerged in the literature. In this paper, we assess the capacity of our algorithm and of two others -PlantScan3D and SimpleTree- to reconstruct the 3D structure of trees. The aim of this reconstruction is to be able to characterize the geometric complexity of trees, with different heights, sizes and shapes of branches. Based on a specific surveying workflow with a TLS, we have acquired dense point clouds of six different urban trees, with specific architectures, before reconstructing them with each algorithm. Finally, qualitative and quantitative assessments of the models are performed using reference tree reconstructions and field measurements. Based on this assessment, the advantages and the limits of every reconstruction algorithm are highlighted. Anyway, very satisfying results can be reached for 3D reconstructions of tree topology as well as of tree volume.

  8. Unlocking the scientific potential of complex 3D point cloud dataset : new classification and 3D comparison methods

    NASA Astrophysics Data System (ADS)

    Lague, D.; Brodu, N.; Leroux, J.

    2012-12-01

    Ground based lidar and photogrammetric techniques are increasingly used to track the evolution of natural surfaces in 3D at an unprecedented resolution and precision. The range of applications encompass many type of natural surfaces with different geometries and roughness characteristics (landslides, cliff erosion, river beds, bank erosion,....). Unravelling surface change in these contexts requires to compare large point clouds in 2D or 3D. The most commonly used method in geomorphology is based on a 2D difference of the gridded point clouds. Yet this is hardly adapted to many 3D natural environments such as rivers (with horizontal beds and vertical banks), while gridding complex rough surfaces is a complex task. On the other hand, tools allowing to perform 3D comparison are scarce and may require to mesh the point clouds which is difficult on rough natural surfaces. Moreover, existing 3D comparison tools do not provide an explicit calculation of confidence intervals that would factor in registration errors, roughness effects and instrument related position uncertainties. To unlock this problem, we developed the first algorithm combining a 3D measurement of surface change directly on point clouds with an estimate of spatially variable confidence intervals (called M3C2). The method has two steps : (1) surface normal estimation and orientation in 3D at a scale consistent with the local roughness ; (2) measurement of mean surface change along the normal direction with explicit calculation of a local confidence interval. Comparison with existing 3D methods based on a closest-point calculation demonstrates the higher precision of the M3C2 method when mm changes needs to be detected. The M3C2 method is also simple to use as it does not require surface meshing or gridding, and is not sensitive to missing data or change in point density. We also present a 3D classification tool (CANUPO) for vegetation removal based on a new geometrical measure: the multi

  9. Extending 3D Near-Cloud Corrections from Shorter to Longer Wavelengths

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    Satellite observations have shown a positive correlation between cloud amount and aerosol optical thickness (AOT) that can be explained by the humidification of aerosols near clouds, and/or by cloud contamination by sub-pixel size clouds and the cloud adjacency effect. The last effect may substantially increase reflected radiation in cloud-free columns, leading to overestimates in the retrieved AOT. For clear-sky areas near boundary layer clouds the main contribution to the enhancement of clear sky reflectance at shorter wavelengths comes from the radiation scattered into clear areas by clouds and then scattered to the sensor by air molecules. Because of the wavelength dependence of air molecule scattering, this process leads to a larger reflectance increase at shorter wavelengths, and can be corrected using a simple two-layer model. However, correcting only for molecular scattering skews spectral properties of the retrieved AOT. Kassianov and Ovtchinnikov proposed a technique that uses spectral reflectance ratios to retrieve AOT in the vicinity of clouds; they assumed that the cloud adjacency effect influences the spectral ratio between reflectances at two wavelengths less than it influences the reflectances themselves. This paper combines the two approaches: It assumes that the 3D correction for the shortest wavelength is known with some uncertainties, and then it estimates the 3D correction for longer wavelengths using a modified ratio method. The new approach is tested with 3D radiances simulated for 26 cumulus fields from Large-Eddy Simulations, supplemented with 40 aerosol profiles. The results showed that (i) for a variety of cumulus cloud scenes and aerosol profiles over ocean the 3D correction due to cloud adjacency effect can be extended from shorter to longer wavelengths and (ii) the 3D corrections for longer wavelengths are not very sensitive to unbiased random uncertainties in the 3D corrections at shorter wavelengths.

  10. Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction

    SciTech Connect

    Alexander Marshak; Warren Wiscombe; Yuri Knyazikhin; Christine Chiu

    2011-05-24

    We proposed a variety of tasks centered on the following question: what can we learn about 3D cloud-radiation processes and aerosol-cloud interaction from rapid-sampling ARM measurements of spectral zenith radiance? These ARM measurements offer spectacular new and largely unexploited capabilities in both the temporal and spectral domains. Unlike most other ARM instruments, which average over many seconds or take samples many seconds apart, the new spectral zenith radiance measurements are fast enough to resolve natural time scales of cloud change and cloud boundaries as well as the transition zone between cloudy and clear areas. In the case of the shortwave spectrometer, the measurements offer high time resolution and high spectral resolution, allowing new discovery-oriented science which we intend to pursue vigorously. Research objectives are, for convenience, grouped under three themes: • Understand radiative signature of the transition zone between cloud-free and cloudy areas using data from ARM shortwave radiometers, which has major climatic consequences in both aerosol direct and indirect effect studies. • Provide cloud property retrievals from the ARM sites and the ARM Mobile Facility for studies of aerosol-cloud interactions. • Assess impact of 3D cloud structures on aerosol properties using passive and active remote sensing techniques from both ARM and satellite measurements.

  11. 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.

  12. 3D-resolved targeting of photodynamic therapy using temporal focusing

    PubMed Central

    Rowlands, Christopher J; Wu, Jackie; Uzel, Sebastien G M; Klein, Oliver; Evans, Conor L; So, Peter T C

    2014-01-01

    A method for selectively inducing apoptosis in tumor nodules is presented, with close-to-cellular level resolution, using 3D-resolved widefield temporal focusing illumination. Treatment times on the order of seconds were achieved using Verteporfin as the photosensitizer, with doses of 30 μg ml−1 and below. Results were achieved on both 2D and 3D cell cultures, demonstrating that treatment was possible through approximately one hundred microns of dense tumor nodules. PMID:25620902

  13. Automated Mosaicking of Multiple 3d Point Clouds Generated from a Depth Camera

    NASA Astrophysics Data System (ADS)

    Kim, H.; Yoon, W.; Kim, T.

    2016-06-01

    In this paper, we propose a method for automated mosaicking of multiple 3D point clouds generated from a depth camera. A depth camera generates depth data by using ToF (Time of Flight) method and intensity data by using intensity of returned signal. The depth camera used in this paper was a SR4000 from MESA Imaging. This camera generates a depth map and intensity map of 176 x 44 pixels. Generated depth map saves physical depth data with mm of precision. Generated intensity map contains texture data with many noises. We used texture maps for extracting tiepoints and depth maps for assigning z coordinates to tiepoints and point cloud mosaicking. There are four steps in the proposed mosaicking method. In the first step, we acquired multiple 3D point clouds by rotating depth camera and capturing data per rotation. In the second step, we estimated 3D-3D transformation relationships between subsequent point clouds. For this, 2D tiepoints were extracted automatically from the corresponding two intensity maps. They were converted into 3D tiepoints using depth maps. We used a 3D similarity transformation model for estimating the 3D-3D transformation relationships. In the third step, we converted local 3D-3D transformations into a global transformation for all point clouds with respect to a reference one. In the last step, the extent of single depth map mosaic was calculated and depth values per mosaic pixel were determined by a ray tracing method. For experiments, 8 depth maps and intensity maps were used. After the four steps, an output mosaicked depth map of 454x144 was generated. It is expected that the proposed method would be useful for developing an effective 3D indoor mapping method in future.

  14. The Engelbourg's ruins: from 3D TLS point cloud acquisition to 3D virtual and historic models

    NASA Astrophysics Data System (ADS)

    Koehl, Mathieu; Berger, Solveig; Nobile, Sylvain

    2014-05-01

    The Castle of Engelbourg was built at the beginning of the 13th century, at the top of the Schlossberg. It is situated on the territory of the municipality of Thann (France), at the crossroads of Alsace and Lorraine, and dominates the outlet of the valley of Thur. Its strategic position was one of the causes of its systematic destructions during the 17th century, and Louis XIV finished his fate by ordering his demolition in 1673. Today only few vestiges remain, of which a section of the main tower from about 7m of diameter and 4m of wide laying on its slice, unique characteristic in the regional castral landscape. It is visible since the valley, was named "the Eye of the witch", and became a key attraction of the region. The site, which extends over approximately one hectare, is for several years the object of numerous archaeological studies and is at the heart of a project of valuation of the vestiges today. It was indeed a key objective, among the numerous planned works, to realize a 3D model of the site in its current state, in other words, a virtual model "such as seized", exploitable as well from a cultural and tourist point of view as by scientists and in archaeological researches. The team of the ICube/INSA lab had in responsibility the realization of this model, the acquisition of the data until the delivery of the virtual model, thanks to 3D TLS and topographic surveying methods. It was also planned to integrate into this 3D model, data of 2D archives, stemming from series of former excavations. The objectives of this project were the following ones: • Acquisition of 3D digital data of the site and 3D modelling • Digitization of the 2D archaeological data and integration in the 3D model • Implementation of a database connected to the 3D model • Virtual Visit of the site The obtained results allowed us to visualize every 3D object individually, under several forms (point clouds, 3D meshed objects and models, etc.) and at several levels of detail

  15. Comparison of 3D interest point detectors and descriptors for point cloud fusion

    NASA Astrophysics Data System (ADS)

    Hänsch, R.; Weber, T.; Hellwich, O.

    2014-08-01

    The extraction and description of keypoints as salient image parts has a long tradition within processing and analysis of 2D images. Nowadays, 3D data gains more and more importance. This paper discusses the benefits and limitations of keypoints for the task of fusing multiple 3D point clouds. For this goal, several combinations of 3D keypoint detectors and descriptors are tested. The experiments are based on 3D scenes with varying properties, including 3D scanner data as well as Kinect point clouds. The obtained results indicate that the specific method to extract and describe keypoints in 3D data has to be carefully chosen. In many cases the accuracy suffers from a too strong reduction of the available points to keypoints.

  16. A 3D Current Loop Model of Magnetic Clouds

    NASA Astrophysics Data System (ADS)

    Chen, James

    1992-05-01

    A magnetohydrodynamic (MHD) model is developed to study magnetic clouds (Burlaga et al. 1981). In this model, magnetic clouds observed near 1 AU are treated as a consequence of eruptive solar current loops. It is shown that current loops intially in MHD equilibrium can be triggered to rise rapidly, propelling material of up to 10(16) g at up to ~ 1000 km s(-1) and dissipating ~ 10(32) erg of magnetic energy in tens of minutes. The initial rise profile is consistent with observed height-time profiles of erupting filaments (Kahler et al. 1988). Two triggering mechanisms for eruption are suggested: (1)subphotospheric energy storage and trigger and (2) in situ (coronal) energy storage and trigger. In the former, eruption occurs as a result of changes in the subphotospheric magnetic topology and subsequent relaxation to a new equilibrium. In the latter, the current loop can evolve to exceed a local maximum in the magnetic potential associated with the ambient magnetic fields. The former scenario leads to more energetic and longer-lasting eruption than the latter. Burlaga, L. F., Sittler, E., Mariani, F., and Schwenn, R. 1981, J. Geophys. Res., 86, 6673. Kahler, S. W., Moore, R. L., Kane, S. R., and Zirin, H. 1988, Ap. J., 328, 824.

  17. Filtering method for 3D laser scanning point cloud

    NASA Astrophysics Data System (ADS)

    Liu, Da; Wang, Li; Hao, Yuncai; Zhang, Jun

    2015-10-01

    In recent years, with the rapid development of the hardware and software of the three-dimensional model acquisition, three-dimensional laser scanning technology is utilized in various aspects, especially in space exploration. The point cloud filter is very important before using the data. In the paper, considering both the processing quality and computing speed, an improved mean-shift point cloud filter method is proposed. Firstly, by analyze the relevance of the normal vector between the upcoming processing point and the near points, the iterative neighborhood of the mean-shift is selected dynamically, then the high frequency noise is constrained. Secondly, considering the normal vector of the processing point, the normal vector is updated. Finally, updated position is calculated for each point, then each point is moved in the normal vector according to the updated position. The experimental results show that the large features are retained, at the same time, the small sharp features are also existed for different size and shape of objects, so the target feature information is protected precisely. The computational complexity of the proposed method is not high, it can bring high precision results with fast speed, so it is very suitable for space application. It can also be utilized in civil, such as large object measurement, industrial measurement, car navigation etc. In the future, filter with the help of point strength will be further exploited.

  18. Effects of 3-D thermal radiation on the development of a shallow cumulus cloud field

    NASA Astrophysics Data System (ADS)

    Klinger, Carolin; Mayer, Bernhard; Jakub, Fabian; Zinner, Tobias; Park, Seung-Bu; Gentine, Pierre

    2017-04-01

    We investigate the effects of thermal radiation on cloud development in large-eddy simulations (LESs) with the UCLA-LES model. We investigate single convective clouds (driven by a warm bubble) at 50 m horizontal resolution and a large cumulus cloud field at 50 and 100 m horizontal resolutions. We compare the newly developed 3-D Neighboring Column Approximation with the independent column approximation and a simulation without radiation and their respective impact on clouds. Thermal radiation causes strong local cooling at cloud tops accompanied by a modest warming at the cloud bottom and, in the case of the 3-D scheme, also cloud side cooling. 3-D thermal radiation causes systematically larger cooling when averaged over the model domain. In order to investigate the effects of local cooling on the clouds and to separate these local effects from a systematically larger cooling effect in the modeling domain, we apply the radiative transfer solutions in different ways. The direct effect of heating and cooling at the clouds is applied (local thermal radiation) in a first simulation. Furthermore, a horizontal average of the 1-D and 3-D radiation in each layer is used to study the effect of local cloud radiation as opposed to the domain-averaged effect. These averaged radiation simulations exhibit a cooling profile with stronger cooling in the cloudy layers. In a final setup, we replace the radiation simulation by a uniform cooling of 2.6 K day-1. To focus on the radiation effects themselves and to avoid possible feedbacks, we fixed surface fluxes of latent and sensible heat and omitted the formation of rain in our simulations. Local thermal radiation changes cloud circulation in the single cloud simulations, as well as in the shallow cumulus cloud field, by causing stronger updrafts and stronger subsiding shells. In our cumulus cloud field simulation, we find that local radiation enhances the circulation compared to the averaged radiation applications. In addition, we

  19. Parameterization and Analysis of 3-D Solar Radiative Transfer in Clouds: Final Report

    SciTech Connect

    Jerry Y. Harrington

    2012-09-21

    This document reports on the research that we have done over the course of our two-year project. The report also covers the research done on this project during a 1 year no-cost extension of the grant. Our work has had two main, inter-related thrusts: The first thrust was to characterize the response of stratocumulus cloud structure and dynamics to systematic changes in cloud infrared radiative cooling and solar heating using one-dimensional radiative transfer models. The second was to couple a three-dimensional (3-D) solar radiative transfer model to the Large Eddy Simulation (LES) model that we use to simulate stratocumulus. The purpose of the studies with 3-D radiative transfer was to examine the possible influences of 3-D photon transport on the structure, evolution, and radiative properties of stratocumulus. While 3-D radiative transport has been examined in static cloud environments, few studies have attempted to examine whether the 3-D nature of radiative absorption and emission influence the structure and evolution of stratocumulus. We undertook this dual approach because only a small number of LES simulations with the 3-D radiative transfer model are possible due to the high computational costs. Consequently, LES simulations with a 1-D radiative transfer solver were used in order to examine the portions of stratocumulus parameter space that may be most sensitive to perturbations in the radiative fields. The goal was then to explore these sensitive regions with LES using full 3-D radiative transfer. Our overall goal was to discover whether 3-D radiative processes alter cloud structure and evolution, and whether this may have any indirect implications for cloud radiative properties. In addition, we collaborated with Dr. Tamas Varni, providing model output fields for his attempt at parameterizing 3-D radiative effects for cloud models.

  20. Representing 3-D cloud radiation effects in two-stream schemes: 1. Longwave considerations and effective cloud edge length

    NASA Astrophysics Data System (ADS)

    Schäfer, Sophia A. K.; Hogan, Robin J.; Klinger, Carolin; Chiu, J. Christine; Mayer, Bernhard

    2016-07-01

    Current weather and climate models neglect 3-D radiative transfer through cloud sides, which can change the cloud radiative effect (CRE) significantly. This two-part paper describes the development of the SPeedy Algorithm for Radiative TrAnsfer through CloUd Sides (SPARTACUS) to capture these effects efficiently in a two-stream radiation scheme for use in global models. The present paper concerns the longwave spectral region, where not much work has been done previously, although the limited previous work has suggested that radiative transfer through cloud sides increases the longwave surface CRE of shallow cumulus by around 30%. To assist the development of a longwave capability for SPARTACUS, we use a reference case of an isolated, isothermal, optically thick, cubic cloud in vacuum, for which 3-D effects increase CRE by exactly 200%. It is shown that for any cloud shape, the 3-D effect can be represented in SPARTACUS provided that correct account is made for (1) the effective zenith angle of diffuse radiation emitted from a cloud, (2) the spatial distribution of fluxes in the cloud, (3) cloud clustering that enhances the interception of emitted radiation by neighboring clouds, and (4) radiative smoothing leading to the effective cloud edge length being less than the measured value. We find empirically that the circumference of an ellipse fitted to a horizontal cross section through a cumulus cloud provides a good estimate of the radiatively effective cloud edge length, which provides some guidance to how cloud observations could be analyzed to extract their most important properties for radiation.

  1. Fitting a Point Cloud to a 3d Polyhedral Surface

    NASA Astrophysics Data System (ADS)

    Popov, E. V.; Rotkov, S. I.

    2017-05-01

    The ability to measure parameters of large-scale objects in a contactless fashion has a tremendous potential in a number of industrial applications. However, this problem is usually associated with an ambiguous task to compare two data sets specified in two different co-ordinate systems. This paper deals with the study of fitting a set of unorganized points to a polyhedral surface. The developed approach uses Principal Component Analysis (PCA) and Stretched grid method (SGM) to substitute a non-linear problem solution with several linear steps. The squared distance (SD) is a general criterion to control the process of convergence of a set of points to a target surface. The described numerical experiment concerns the remote measurement of a large-scale aerial in the form of a frame with a parabolic shape. The experiment shows that the fitting process of a point cloud to a target surface converges in several linear steps. The method is applicable to the geometry remote measurement of large-scale objects in a contactless fashion.

  2. 3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

    NASA Technical Reports Server (NTRS)

    Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

    2007-01-01

    3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

  3. Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; Zinner, Tobias; Ackerman, S.

    2008-01-01

    Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

  4. Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

    NASA Technical Reports Server (NTRS)

    Platnick, Steven; Zinner, Tobias; Ackerman, S.

    2008-01-01

    Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

  5. Quantitative analyses of the 3D nuclear landscape recorded with super-resolved fluorescence microscopy.

    PubMed

    Schmid, Volker J; Cremer, Marion; Cremer, Thomas

    2017-03-18

    Recent advancements of super-resolved fluorescence microscopy have revolutionized microscopic studies of cells, including the exceedingly complex structural organization of cell nuclei in space and time. In this paper we describe and discuss tools for (semi-) automated, quantitative 3D analyses of the spatial nuclear organization. These tools allow the quantitative assessment of highly resolved different chromatin compaction levels in individual cell nuclei, which reflect functionally different regions or sub-compartments of the 3D nuclear landscape, and measurements of absolute distances between sites of different chromatin compaction. In addition, these tools allow 3D mapping of specific DNA/RNA sequences and nuclear proteins relative to the 3D chromatin compaction maps and comparisons of multiple cell nuclei. The tools are available in the free and open source R packages nucim and bioimagetools. We discuss the use of masks for the segmentation of nuclei and the use of DNA stains, such as DAPI, as a proxy for local differences in chromatin compaction. We further discuss the limitations of 3D maps of the nuclear landscape as well as problems of the biological interpretation of such data.

  6. Dynamic mineral clouds on HD 189733b. I. 3D RHD with kinetic, non-equilibrium cloud formation

    NASA Astrophysics Data System (ADS)

    Lee, G.; Dobbs-Dixon, I.; Helling, Ch.; Bognar, K.; Woitke, P.

    2016-10-01

    Context. Observations of exoplanet atmospheres have revealed the presence of cloud particles in their atmospheres. 3D modelling of cloud formation in atmospheres of extrasolar planets coupled to the atmospheric dynamics has long been a challenge. Aims: We investigate the thermo-hydrodynamic properties of cloud formation processes in the atmospheres of hot Jupiter exoplanets. Methods: We simulate the dynamic atmosphere of HD 189733b with a 3D model that couples 3D radiative-hydrodynamics with a kinetic, microphysical mineral cloud formation module designed for RHD/GCM exoplanet atmosphere simulations. Our simulation includes the feedback effects of cloud advection and settling, gas phase element advection and depletion/replenishment and the radiative effects of cloud opacity. We model the cloud particles as a mix of mineral materials which change in size and composition as they travel through atmospheric thermo-chemical environments. All local cloud properties such as number density, grain size and material composition are time-dependently calculated. Gas phase element depletion as a result of cloud formation is included in the model. In situ effective medium theory and Mie theory is applied to calculate the wavelength dependent opacity of the cloud component. Results: We present a 3D cloud structure of a chemically complex, gaseous atmosphere of the hot Jupiter HD 189733b. Mean cloud particle sizes are typically sub-micron (0.01-0.5 μm) at pressures less than 1 bar with hotter equatorial regions containing the smallest grains. Denser cloud structures occur near terminator regions and deeper (~1 bar) atmospheric layers. Silicate materials such as MgSiO3[s] are found to be abundant at mid-high latitudes, while TiO2[s] and SiO2[s] dominate the equatorial regions. Elements involved in the cloud formation can be depleted by several orders of magnitude. Conclusions: The interplay between radiative-hydrodynamics and cloud kinetics leads to an inhomogeneous, wavelength

  7. Reconstruction of Consistent 3d CAD Models from Point Cloud Data Using a Priori CAD Models

    NASA Astrophysics Data System (ADS)

    Bey, A.; Chaine, R.; Marc, R.; Thibault, G.; Akkouche, S.

    2011-09-01

    We address the reconstruction of 3D CAD models from point cloud data acquired in industrial environments, using a pre-existing 3D model as an initial estimate of the scene to be processed. Indeed, this prior knowledge can be used to drive the reconstruction so as to generate an accurate 3D model matching the point cloud. We more particularly focus our work on the cylindrical parts of the 3D models. We propose to state the problem in a probabilistic framework: we have to search for the 3D model which maximizes some probability taking several constraints into account, such as the relevancy with respect to the point cloud and the a priori 3D model, and the consistency of the reconstructed model. The resulting optimization problem can then be handled using a stochastic exploration of the solution space, based on the random insertion of elements in the configuration under construction, coupled with a greedy management of the conflicts which efficiently improves the configuration at each step. We show that this approach provides reliable reconstructed 3D models by presenting some results on industrial data sets.

  8. 3D point cloud registration based on the assistant camera and Harris-SIFT

    NASA Astrophysics Data System (ADS)

    Zhang, Yue; Yu, HongYang

    2016-07-01

    3D(Three-Dimensional) point cloud registration technology is the hot topic in the field of 3D reconstruction, but most of the registration method is not real-time and ineffective. This paper proposes a point cloud registration method of 3D reconstruction based on Harris-SIFT and assistant camera. The assistant camera is used to pinpoint mobile 3D reconstruction device, The feature points of images are detected by using Harris operator, the main orientation for each feature point is calculated, and lastly, the feature point descriptors are generated after rotating the coordinates of the descriptors relative to the feature points' main orientations. Experimental results of demonstrate the effectiveness of the proposed method.

  9. 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.

  10. Dense 3d Point Cloud Generation from Uav Images from Image Matching and Global Optimazation

    NASA Astrophysics Data System (ADS)

    Rhee, S.; Kim, T.

    2016-06-01

    3D spatial information from unmanned aerial vehicles (UAV) images is usually provided in the form of 3D point clouds. For various UAV applications, it is important to generate dense 3D point clouds automatically from over the entire extent of UAV images. In this paper, we aim to apply image matching for generation of local point clouds over a pair or group of images and global optimization to combine local point clouds over the whole region of interest. We tried to apply two types of image matching, an object space-based matching technique and an image space-based matching technique, and to compare the performance of the two techniques. The object space-based matching used here sets a list of candidate height values for a fixed horizontal position in the object space. For each height, its corresponding image point is calculated and similarity is measured by grey-level correlation. The image space-based matching used here is a modified relaxation matching. We devised a global optimization scheme for finding optimal pairs (or groups) to apply image matching, defining local match region in image- or object- space, and merging local point clouds into a global one. For optimal pair selection, tiepoints among images were extracted and stereo coverage network was defined by forming a maximum spanning tree using the tiepoints. From experiments, we confirmed that through image matching and global optimization, 3D point clouds were generated successfully. However, results also revealed some limitations. In case of image-based matching results, we observed some blanks in 3D point clouds. In case of object space-based matching results, we observed more blunders than image-based matching ones and noisy local height variations. We suspect these might be due to inaccurate orientation parameters. The work in this paper is still ongoing. We will further test our approach with more precise orientation parameters.

  11. Segmentation of UAV-based images incorporating 3D point cloud information

    NASA Astrophysics Data System (ADS)

    Vetrivel, A.; Gerke, M.; Kerle, N.; Vosselman, G.

    2015-03-01

    Numerous applications related to urban scene analysis demand automatic recognition of buildings and distinct sub-elements. For example, if LiDAR data is available, only 3D information could be leveraged for the segmentation. However, this poses several risks, for instance, the in-plane objects cannot be distinguished from their surroundings. On the other hand, if only image based segmentation is performed, the geometric features (e.g., normal orientation, planarity) are not readily available. This renders the task of detecting the distinct sub-elements of the building with similar radiometric characteristic infeasible. In this paper the individual sub-elements of buildings are recognized through sub-segmentation of the building using geometric and radiometric characteristics jointly. 3D points generated from Unmanned Aerial Vehicle (UAV) images are used for inferring the geometric characteristics of roofs and facades of the building. However, the image-based 3D points are noisy, error prone and often contain gaps. Hence the segmentation in 3D space is not appropriate. Therefore, we propose to perform segmentation in image space using geometric features from the 3D point cloud along with the radiometric features. The initial detection of buildings in 3D point cloud is followed by the segmentation in image space using the region growing approach by utilizing various radiometric and 3D point cloud features. The developed method was tested using two data sets obtained with UAV images with a ground resolution of around 1-2 cm. The developed method accurately segmented most of the building elements when compared to the plane-based segmentation using 3D point cloud alone.

  12. A Radiative Transfer Case Study for 3-d cloud effects in the UV

    NASA Astrophysics Data System (ADS)

    Meerkötter, Ralf; Degünther, Markus

    Satellite UV mapping is usually based on the independent pixel approximation (IPA) which neglects horizontal photon transport between adjacent columns. Horizontal inhomogeneity of cloud fields therefore causes uncertainties in the derived UV radiation fields. While these effects are small for large pixel satellites, the broken-cloud errors increase as the pixel size decreases. By comparing results of 1-d and 3-d UV radiative transfer calculations for three selected cloud scenes that cover a rather broad range of cloud inhomogeneity the main 3-d cloud effects on the atmospheric UV transmission are identified and quantified in their order of magnitude. With respect to the different spatial resolutions of satellite instruments it is further shown how 3-d cloud effects average out with increasing spatial scale. It turns out that locally the IPA cause maximum uncertainties up to ±100% for a spatial resolution of about 1 × 1 km² (e.g., AVHRR), they are reduced to ±10% for a resolution of about 15 × 15 km² and below 5% for a resolution greater than 30 km (e.g., TOMS).

  13. 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

  14. Recent Advances in 3D Time-Resolved Contrast-Enhanced MR Angiography

    PubMed Central

    Riederer, Stephen J.; Haider, Clifton R.; Borisch, Eric A.; Weavers, Paul T.; Young, Phillip M.

    2015-01-01

    Contrast-enhanced MR angiography (CE-MRA) was first introduced for clinical studies approximately 20 years ago. Early work provided 3 to 4 mm spatial resolution with acquisition times in the 30 sec range. Since that time there has been continuing effort to provide improved spatial resolution with reduced acquisition time, allowing high resolution three-dimensional (3D) time-resolved studies. The purpose of this work is to describe how this has been accomplished. Specific technical enablers have been: improved gradients allowing reduced repetition times, improved k-space sampling and reconstruction methods, parallel acquisition particularly in two directions, and improved and higher count receiver coil arrays. These have collectively made high resolution time-resolved studies readily available for many anatomic regions. Depending on the application, approximate 1 mm isotropic resolution is now possible with frame times of several seconds. Clinical applications of time-resolved CE-MRA are briefly reviewed. PMID:26032598

  15. Recent advances in 3D time-resolved contrast-enhanced MR angiography.

    PubMed

    Riederer, Stephen J; Haider, Clifton R; Borisch, Eric A; Weavers, Paul T; Young, Phillip M

    2015-07-01

    Contrast-enhanced magnetic resonance angiography (CE-MRA) was first introduced for clinical studies approximately 20 years ago. Early work provided 3-4 mm spatial resolution with acquisition times in the 30-second range. Since that time there has been continuing effort to provide improved spatial resolution with reduced acquisition time, allowing high resolution 3D time-resolved studies. The purpose of this work is to describe how this has been accomplished. Specific technical enablers have been: improved gradients allowing reduced repetition times, improved k-space sampling and reconstruction methods, parallel acquisition, particularly in two directions, and improved and higher count receiver coil arrays. These have collectively made high-resolution time-resolved studies readily available for many anatomic regions. Depending on the application, ∼1 mm isotropic resolution is now possible with frame times of several seconds. Clinical applications of time-resolved CE-MRA are briefly reviewed. © 2015 Wiley Periodicals, Inc.

  16. Contextual Classification of Point Cloud Data by Exploiting Individual 3d Neigbourhoods

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Schmidt, A.; Mallet, C.; Hinz, S.; Rottensteiner, F.; Jutzi, B.

    2015-03-01

    The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches rely on the results of a point cloud classification, where each 3D point is assigned a respective semantic class label. Such an assignment, in turn, typically involves statistical methods for feature extraction and machine learning. Whereas the different components in the processing workflow have extensively, but separately been investigated in recent years, the respective connection by sharing the results of crucial tasks across all components has not yet been addressed. This connection not only encapsulates the interrelated issues of neighborhood selection and feature extraction, but also the issue of how to involve spatial context in the classification step. In this paper, we present a novel and generic approach for 3D scene analysis which relies on (i) individually optimized 3D neighborhoods for (ii) the extraction of distinctive geometric features and (iii) the contextual classification of point cloud data. For a labeled benchmark dataset, we demonstrate the beneficial impact of involving contextual information in the classification process and that using individual 3D neighborhoods of optimal size significantly increases the quality of the results for both pointwise and contextual classification.

  17. Fast Probabilistic Fusion of 3d Point Clouds via Occupancy Grids for Scene Classification

    NASA Astrophysics Data System (ADS)

    Kuhn, Andreas; Huang, Hai; Drauschke, Martin; Mayer, Helmut

    2016-06-01

    High resolution consumer cameras on Unmanned Aerial Vehicles (UAVs) allow for cheap acquisition of highly detailed images, e.g., of urban regions. Via image registration by means of Structure from Motion (SfM) and Multi View Stereo (MVS) the automatic generation of huge amounts of 3D points with a relative accuracy in the centimeter range is possible. Applications such as semantic classification have a need for accurate 3D point clouds, but do not benefit from an extremely high resolution/density. In this paper, we, therefore, propose a fast fusion of high resolution 3D point clouds based on occupancy grids. The result is used for semantic classification. In contrast to state-of-the-art classification methods, we accept a certain percentage of outliers, arguing that they can be considered in the classification process when a per point belief is determined in the fusion process. To this end, we employ an octree-based fusion which allows for the derivation of outlier probabilities. The probabilities give a belief for every 3D point, which is essential for the semantic classification to consider measurement noise. For an example point cloud with half a billion 3D points (cf. Figure 1), we show that our method can reduce runtime as well as improve classification accuracy and offers high scalability for large datasets.

  18. 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

  19. Dense point-cloud creation using superresolution for a monocular 3D reconstruction system

    NASA Astrophysics Data System (ADS)

    Diskin, Yakov; Asari, Vijayan K.

    2012-05-01

    We present an enhanced 3D reconstruction algorithm designed to support an autonomously navigated unmanned aerial system (UAS). The algorithm presented focuses on the 3D reconstruction of a scene using only a single moving camera. In this way, the system can be used to construct a point cloud model of its unknown surroundings. The original reconstruction process, resulting with a point cloud was computed based on feature matching and depth triangulation analysis. Although dense, this original model was hindered due to its low disparity resolution. As feature points were matched from frame to frame, the resolution of the input images and the discrete nature of disparities limited the depth computations within a scene. With the recent addition of the preprocessing steps of nonlinear super resolution, the accuracy of the point cloud which relies on precise disparity measurement has significantly increased. Using a pixel by pixel approach, the super resolution technique computes the phase congruency of each pixel's neighborhood and produces nonlinearly interpolated high resolution input frames. Thus, a feature point travels a more precise discrete disparity. Also, the quantity of points within the 3D point cloud model is significantly increased since the number of features is directly proportional to the resolution and high frequencies of the input image. The contribution of the newly added preprocessing steps is measured by evaluating the density and accuracy of the reconstructed point cloud for autonomous navigation and mapping tasks within unknown environments.

  20. Facets : a Cloudcompare Plugin to Extract Geological Planes from Unstructured 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Dewez, T. J. B.; Girardeau-Montaut, D.; Allanic, C.; Rohmer, J.

    2016-06-01

    Geological planar facets (stratification, fault, joint…) are key features to unravel the tectonic history of rock outcrop or appreciate the stability of a hazardous rock cliff. Measuring their spatial attitude (dip and strike) is generally performed by hand with a compass/clinometer, which is time consuming, requires some degree of censoring (i.e. refusing to measure some features judged unimportant at the time), is not always possible for fractures higher up on the outcrop and is somewhat hazardous. 3D virtual geological outcrop hold the potential to alleviate these issues. Efficiently segmenting massive 3D point clouds into individual planar facets, inside a convenient software environment was lacking. FACETS is a dedicated plugin within CloudCompare v2.6.2 (http://cloudcompare.org/ ) implemented to perform planar facet extraction, calculate their dip and dip direction (i.e. azimuth of steepest decent) and report the extracted data in interactive stereograms. Two algorithms perform the segmentation: Kd-Tree and Fast Marching. Both divide the point cloud into sub-cells, then compute elementary planar objects and aggregate them progressively according to a planeity threshold into polygons. The boundaries of the polygons are adjusted around segmented points with a tension parameter, and the facet polygons can be exported as 3D polygon shapefiles towards third party GIS software or simply as ASCII comma separated files. One of the great features of FACETS is the capability to explore planar objects but also 3D points with normals with the stereogram tool. Poles can be readily displayed, queried and manually segmented interactively. The plugin blends seamlessly into CloudCompare to leverage all its other 3D point cloud manipulation features. A demonstration of the tool is presented to illustrate these different features. While designed for geological applications, FACETS could be more widely applied to any planar

  1. 3-D In Vitro Acoustic Super-Resolution and Super-Resolved Velocity Mapping Using Microbubbles.

    PubMed

    Christensen-Jeffries, Kirsten; Brown, Jemma; Aljabar, Paul; Tang, Mengxing; Dunsby, Christopher; Eckersley, Robert J

    2017-10-01

    Standard clinical ultrasound (US) imaging frequencies are unable to resolve microvascular structures due to the fundamental diffraction limit of US waves. Recent demonstrations of 2-D super-resolution both in vitro and in vivo have demonstrated that fine vascular structures can be visualized using acoustic single bubble localization. Visualization of more complex and disordered 3-D vasculature, such as that of a tumor, requires an acquisition strategy which can additionally localize bubbles in the elevational plane with high precision in order to generate super-resolution in all three dimensions. Furthermore, a particular challenge lies in the need to provide this level of visualization with minimal acquisition time. In this paper, we develop a fast, coherent US imaging tool for microbubble localization in 3-D using a pair of US transducers positioned at 90°. This allowed detection of point scatterer signals in 3-D with average precisions equal to [Formula: see text] in axial and elevational planes, and [Formula: see text] in the lateral plane, compared to the diffraction limited point spread function full-widths at half-maximum of 488, 1188, and [Formula: see text] of the original imaging system with a single transducer. Visualization and velocity mapping of 3-D in vitro structures was demonstrated far beyond the diffraction limit. The capability to measure the complete flow pattern of blood vessels associated with disease at depth would ultimately enable analysis of in vivo microvascular morphology, blood flow dynamics, and occlusions resulting from disease states.

  2. Coherent Microscopy for 3-D Movement Monitoring and Super-Resolved Imaging

    NASA Astrophysics Data System (ADS)

    Beiderman, Yevgeny; Amsel, Avigail; Tzadka, Yaniv; Fixler, Dror; Teicher, Mina; Micó, Vicente; Garcí, Javier; Javidi, Bahram; DaneshPanah, Mehdi; Moon, Inkyu; Zalevsky, Zeev

    In this chapter we present three types of microscopy-related configurations while the first one is used for 3-D movement monitoring of the inspected samples, the second one is used for super-resolved 3-D imaging, and the last one presents an overview digital holographic microscopy applications. The first configuration is based on temporal tracking of secondary reflected speckles when imaged by properly defocused optics. We validate the proposed scheme by using it to monitor 3-D spontaneous contraction of rat's cardiac muscle cells while allowing nanometric tracking accuracy without interferometric recording. The second configuration includes projection of temporally varying speckle patterns on top of the sample and by proper decoding exceeding the diffraction as well as the geometrical-related lateral resolution limitation. In the final part of the chapter, we overview applications of digital holographic microscopy (DHM) for real-time non-invasive 3-D sensing, tracking, and recognition of living microorganisms such as single- or multiple-cell organisms and bacteria.

  3. 3DVEM Software Modules for Efficient Management of Point Clouds and Photorealistic 3d Models

    NASA Astrophysics Data System (ADS)

    Fabado, S.; Seguí, A. E.; Cabrelles, M.; Navarro, S.; García-De-San-Miguel, D.; Lerma, J. L.

    2013-07-01

    Cultural heritage managers in general and information users in particular are not usually used to deal with high-technological hardware and software. On the contrary, information providers of metric surveys are most of the times applying latest developments for real-life conservation and restoration projects. This paper addresses the software issue of handling and managing either 3D point clouds or (photorealistic) 3D models to bridge the gap between information users and information providers as regards the management of information which users and providers share as a tool for decision-making, analysis, visualization and management. There are not many viewers specifically designed to handle, manage and create easily animations of architectural and/or archaeological 3D objects, monuments and sites, among others. 3DVEM - 3D Viewer, Editor & Meter software will be introduced to the scientific community, as well as 3DVEM - Live and 3DVEM - Register. The advantages of managing projects with both sets of data, 3D point cloud and photorealistic 3D models, will be introduced. Different visualizations of true documentation projects in the fields of architecture, archaeology and industry will be presented. Emphasis will be driven to highlight the features of new userfriendly software to manage virtual projects. Furthermore, the easiness of creating controlled interactive animations (both walkthrough and fly-through) by the user either on-the-fly or as a traditional movie file will be demonstrated through 3DVEM - Live.

  4. Retrieval of cloud microphysical parameters from INSAT-3D: a feasibility study using radiative transfer simulations

    NASA Astrophysics Data System (ADS)

    Jinya, John; Bipasha, Paul S.

    2016-05-01

    Clouds strongly modulate the Earths energy balance and its atmosphere through their interaction with the solar and terrestrial radiation. They interact with radiation in various ways like scattering, emission and absorption. By observing these changes in radiation at different wavelength, cloud properties can be estimated. Cloud properties are of utmost importance in studying different weather and climate phenomena. At present, no satellite provides cloud microphysical parameters over the Indian region with high temporal resolution. INSAT-3D imager observations in 6 spectral channels from geostationary platform offer opportunity to study continuous cloud properties over Indian region. Visible (0.65 μm) and shortwave-infrared (1.67 μm) channel radiances can be used to retrieve cloud microphysical parameters such as cloud optical thickness (COT) and cloud effective radius (CER). In this paper, we have carried out a feasibility study with the objective of cloud microphysics retrieval. For this, an inter-comparison of 15 globally available radiative transfer models (RTM) were carried out with the aim of generating a Look-up- Table (LUT). SBDART model was chosen for the simulations. The sensitivity of each spectral channel to different cloud properties was investigated. The inputs to the RT model were configured over our study region (50°S - 50°N and 20°E - 130°E) and a large number of simulations were carried out using random input vectors to generate the LUT. The determination of cloud optical thickness and cloud effective radius from spectral reflectance measurements constitutes the inverse problem and is typically solved by comparing the measured reflectances with entries in LUT and searching for the combination of COT and CER that gives the best fit. The products are available on the website www.mosdac.gov.in

  5. 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.

  6. Feature relevance assessment for the semantic interpretation of 3D point cloud data

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Jutzi, B.; Mallet, C.

    2013-10-01

    The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

  7. Towards semi-automatic rock mass discontinuity orientation and set analysis from 3D point clouds

    NASA Astrophysics Data System (ADS)

    Guo, Jiateng; Liu, Shanjun; Zhang, Peina; Wu, Lixin; Zhou, Wenhui; Yu, Yinan

    2017-06-01

    Obtaining accurate information on rock mass discontinuities for deformation analysis and the evaluation of rock mass stability is important. Obtaining measurements for high and steep zones with the traditional compass method is difficult. Photogrammetry, three-dimensional (3D) laser scanning and other remote sensing methods have gradually become mainstream methods. In this study, a method that is based on a 3D point cloud is proposed to semi-automatically extract rock mass structural plane information. The original data are pre-treated prior to segmentation by removing outlier points. The next step is to segment the point cloud into different point subsets. Various parameters, such as the normal, dip/direction and dip, can be calculated for each point subset after obtaining the equation of the best fit plane for the relevant point subset. A cluster analysis (a point subset that satisfies some conditions and thus forms a cluster) is performed based on the normal vectors by introducing the firefly algorithm (FA) and the fuzzy c-means (FCM) algorithm. Finally, clusters that belong to the same discontinuity sets are merged and coloured for visualization purposes. A prototype system is developed based on this method to extract the points of the rock discontinuity from a 3D point cloud. A comparison with existing software shows that this method is feasible. This method can provide a reference for rock mechanics, 3D geological modelling and other related fields.

  8. Comparison Between Two Generic 3d Building Reconstruction Approaches - Point Cloud Based VS. Image Processing Based

    NASA Astrophysics Data System (ADS)

    Dahlke, D.; Linkiewicz, M.

    2016-06-01

    This paper compares two generic approaches for the reconstruction of buildings. Synthesized and real oblique and vertical aerial imagery is transformed on the one hand into a dense photogrammetric 3D point cloud and on the other hand into photogrammetric 2.5D surface models depicting a scene from different cardinal directions. One approach evaluates the 3D point cloud statistically in order to extract the hull of structures, while the other approach makes use of salient line segments in 2.5D surface models, so that the hull of 3D structures can be recovered. With orders of magnitudes more analyzed 3D points, the point cloud based approach is an order of magnitude more accurate for the synthetic dataset compared to the lower dimensioned, but therefor orders of magnitude faster, image processing based approach. For real world data the difference in accuracy between both approaches is not significant anymore. In both cases the reconstructed polyhedra supply information about their inherent semantic and can be used for subsequent and more differentiated semantic annotations through exploitation of texture information.

  9. 3D MODELING OF GJ1214b's ATMOSPHERE: FORMATION OF INHOMOGENEOUS HIGH CLOUDS AND OBSERVATIONAL IMPLICATIONS

    SciTech Connect

    Charnay, B.; Meadows, V.; Misra, A.; Arney, G.; Leconte, J.

    2015-11-01

    The warm sub-Neptune GJ1214b has a featureless transit spectrum that may be due to the presence of high and thick clouds or haze. Here, we simulate the atmosphere of GJ1214b with a 3D General Circulation Model for cloudy hydrogen-dominated atmospheres, including cloud radiative effects. We show that the atmospheric circulation is strong enough to transport micrometric cloud particles to the upper atmosphere and generally leads to a minimum of cloud at the equator. By scattering stellar light, clouds increase the planetary albedo to 0.4–0.6 and cool the atmosphere below 1 mbar. However, the heating by ZnS clouds leads to the formation of a stratospheric thermal inversion above 10 mbar, with temperatures potentially high enough on the dayside to evaporate KCl clouds. We show that flat transit spectra consistent with Hubble Space Telescope observations are possible if cloud particle radii are around 0.5 μm, and that such clouds should be optically thin at wavelengths >3 μm. Using simulated cloudy atmospheres that fit the observed spectra we generate transit, emission, and reflection spectra and phase curves for GJ1214b. We show that a stratospheric thermal inversion would be readily accessible in near- and mid-infrared atmospheric spectral windows. We find that the amplitude of the thermal phase curves is strongly dependent on metallicity, but only slightly impacted by clouds. Our results suggest that primary and secondary eclipses and phase curves observed by the James Webb Space Telescope in the near- to mid-infrared should provide strong constraints on the nature of GJ1214b's atmosphere and clouds.

  10. Extracting valley-ridge lines from point-cloud-based 3D fingerprint models.

    PubMed

    Pang, Xufang; Song, Zhan; Xie, Wuyuan

    2013-01-01

    3D fingerprinting is an emerging technology with the distinct advantage of touchless operation. More important, 3D fingerprint models contain more biometric information than traditional 2D fingerprint images. However, current approaches to fingerprint feature detection usually must transform the 3D models to a 2D space through unwrapping or other methods, which might introduce distortions. A new approach directly extracts valley-ridge features from point-cloud-based 3D fingerprint models. It first applies the moving least-squares method to fit a local paraboloid surface and represent the local point cloud area. It then computes the local surface's curvatures and curvature tensors to facilitate detection of the potential valley and ridge points. The approach projects those points to the most likely valley-ridge lines, using statistical means such as covariance analysis and cross correlation. To finally extract the valley-ridge lines, it grows the polylines that approximate the projected feature points and removes the perturbations between the sampled points. Experiments with different 3D fingerprint models demonstrate this approach's feasibility and performance.

  11. 3D Cloud Effects in OCO-2 Observations - Evidence and Mitigation

    NASA Astrophysics Data System (ADS)

    Schmidt, Sebastian; Massie, Steven; Iwabuchi, Hironobu; Okamura, Rintaro; Crisp, David

    2016-04-01

    In July 2014, the NASA Orbiting Carbon Observatory (OCO-2) satellite was inserted into the 705-km Afternoon Constellation (A-Train). OCO-2 provides estimates of column-averaged CO2 dry air mixing ratios (XCO2), based on high spectral resolution radiance observations of reflected sunlight in the O2 A-band and in the weak and strong absorption CO2 bands at 1.6 and 2.1 μm. The accuracy requirement for OCO-2 XCO2 retrievals is 1 ppmv on regional scales (> 1000 km). At the single sounding level, inhomogeneous clouds, surface albedo, and aerosols introduce wavelength-dependent perturbations into the sensed radiance fields, affecting the retrieval products. Scattering and shadowing by clouds outside of the field of view (FOV) may be a leading source of error for clear-sky XCO2 retrievals in partially cloudy regions. To understand these effects, we developed a 3D OCO-2 simulator, which uses observations by MODIS (also in the A-Train) and other scene information as input to simulate OCO-2 radiance spectra at the full wavelength resolution of the three bands. It is based on MCARaTS (Monte Carlo Atmospheric Radiative Transfer Simulator) as the 3D radiative transfer solver. The OCO-2 3D simulator was applied to an observed scene near a Total Carbon Column Observing Network (TCCON) station. The 3D calculations reproduced the OCO-2 radiances, including the perturbations due to clouds, at the single sounding level. The analysis further suggests that clouds near an OCO-2 footprint leave systematic spectral imprints on the radiances, which could be parameterized to be included in the retrieval state vector. If successful, this new state vector element could account for 3D effects without the need for operational 3D radiative transfer calculations. This may be the starting point not only for the improved screening of low-level broken boundary layer clouds, but also for mitigating the effects of nearby clouds at the radiance level, thus improving the accuracy of retrievals in

  12. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

    Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical

  13. Spatially resolved spectroscopy across stellar surfaces. I. Using exoplanet transits to analyze 3D stellar atmospheres

    NASA Astrophysics Data System (ADS)

    Dravins, Dainis; Ludwig, Hans-Günter; Dahlén, Erik; Pazira, Hiva

    2017-09-01

    Context. High-precision stellar analyses require hydrodynamic modeling to interpret chemical abundances or oscillation modes. Exoplanet atmosphere studies require stellar background spectra to be known along the transit path while detection of Earth analogs require stellar microvariability to be understood. Hydrodynamic 3D models can be computed for widely different stars but have been tested in detail only for the Sun with its resolved surface features. Model predictions include spectral line shapes, asymmetries, and wavelength shifts, and their center-to-limb changes across stellar disks. Aims: We observe high-resolution spectral line profiles across spatially highly resolved stellar surfaces, which are free from the effects of spatial smearing and rotational broadening present in full-disk spectra, enabling comparisons to synthetic profiles from 3D models. Methods: During exoplanet transits, successive stellar surface portions become hidden and differential spectroscopy between various transit phases provides spectra of small surface segments temporarily hidden behind the planet. Planets cover no more than 1% of any main-sequence star, enabling high spatial resolution but demanding very precise observations. Realistically measurable quantities are identified through simulated observations of synthetic spectral lines. Results: In normal stars, line profile ratios between various transit phases may vary by 0.5%, requiring S/N ≳ 5000 for meaningful spectral reconstruction. While not yet realistic for individual spectral lines, this is achievable for cool stars by averaging over numerous lines with similar parameters. Conclusions: For bright host stars of large transiting planets, spatially resolved spectroscopy is currently practical. More observable targets are likely to be found in the near future by ongoing photometric searches.

  14. Comparative Analysis of 3d Point Clouds Generated from a Freeware and Terrestrial Laser Scanner

    NASA Astrophysics Data System (ADS)

    Dayal, K. R.; Raghavendra, S.; Pande, H.; Tiwari, P. S.; Chauhan, I.

    2017-07-01

    In the recent past, several heritage structures have faced destruction due to both human-made incidents and natural calamities that have caused a great loss to the human race regarding its cultural achievements. In this context, the importance of documenting such structures to create a substantial database cannot be emphasised enough. The Clock Tower of Dehradun, India is one such structure. There is a lack of sufficient information in the digital domain, which justified the need to carry out this study. Thus, an attempt has been made to gauge the possibilities of using open source 3D tools such as VSfM to quickly and easily obtain point clouds of an object and assess its quality. The photographs were collected using consumer grade cameras with reasonable effort to ensure overlap. The sparse reconstruction and dense reconstruction were carried out to generate a 3D point cloud model of the tower. A terrestrial laser scanner (TLS) was also used to obtain a point cloud of the tower. The point clouds obtained from the two methods were analyzed to understand the quality of the information present; TLS acquired point cloud being a benchmark to assess the VSfM point cloud. They were compared to analyze the point density and subjected to a plane-fitting test for sample flat portions on the structure. The plane-fitting test revealed the planarity of the point clouds. A Gauss distribution fit yielded a standard deviation of 0.002 and 0.01 for TLS and VSfM, respectively. For more insight, comparisons with Agisoft Photoscan results were also made.

  15. Adaptive noise suppression technique for dense 3D point cloud reconstructions from monocular vision

    NASA Astrophysics Data System (ADS)

    Diskin, Yakov; Asari, Vijayan K.

    2012-10-01

    Mobile vision-based autonomous vehicles use video frames from multiple angles to construct a 3D model of their environment. In this paper, we present a post-processing adaptive noise suppression technique to enhance the quality of the computed 3D model. Our near real-time reconstruction algorithm uses each pair of frames to compute the disparities of tracked feature points to translate the distance a feature has traveled within the frame in pixels into real world depth values. As a result these tracked feature points are plotted to form a dense and colorful point cloud. Due to the inevitable small vibrations in the camera and the mismatches within the feature tracking algorithm, the point cloud model contains a significant amount of misplaced points appearing as noise. The proposed noise suppression technique utilizes the spatial information of each point to unify points of similar texture and color into objects while simultaneously removing noise dissociated with any nearby objects. The noise filter combines all the points of similar depth into 2D layers throughout the point cloud model. By applying erosion and dilation techniques we are able to eliminate the unwanted floating points while retaining points of larger objects. To reverse the compression process, we transform the 2D layer back into the 3D model allowing points to return to their original position without the attached noise components. We evaluate the resulting noiseless point cloud by utilizing an unmanned ground vehicle to perform obstacle avoidance tasks. The contribution of the noise suppression technique is measured by evaluating the accuracy of the 3D reconstruction.

  16. Automated interpretation of 3D laserscanned point clouds for plant organ segmentation.

    PubMed

    Wahabzada, Mirwaes; Paulus, Stefan; Kersting, Kristian; Mahlein, Anne-Katrin

    2015-08-08

    Plant organ segmentation from 3D point clouds is a relevant task for plant phenotyping and plant growth observation. Automated solutions are required to increase the efficiency of recent high-throughput plant phenotyping pipelines. However, plant geometrical properties vary with time, among observation scales and different plant types. The main objective of the present research is to develop a fully automated, fast and reliable data driven approach for plant organ segmentation. The automated segmentation of plant organs using unsupervised, clustering methods is crucial in cases where the goal is to get fast insights into the data or no labeled data is available or costly to achieve. For this we propose and compare data driven approaches that are easy-to-realize and make the use of standard algorithms possible. Since normalized histograms, acquired from 3D point clouds, can be seen as samples from a probability simplex, we propose to map the data from the simplex space into Euclidean space using Aitchisons log ratio transformation, or into the positive quadrant of the unit sphere using square root transformation. This, in turn, paves the way to a wide range of commonly used analysis techniques that are based on measuring the similarities between data points using Euclidean distance. We investigate the performance of the resulting approaches in the practical context of grouping 3D point clouds and demonstrate empirically that they lead to clustering results with high accuracy for monocotyledonous and dicotyledonous plant species with diverse shoot architecture. An automated segmentation of 3D point clouds is demonstrated in the present work. Within seconds first insights into plant data can be deviated - even from non-labelled data. This approach is applicable to different plant species with high accuracy. The analysis cascade can be implemented in future high-throughput phenotyping scenarios and will support the evaluation of the performance of different plant

  17. Automatic pole-like object modeling via 3D part-based analysis of point cloud

    NASA Astrophysics Data System (ADS)

    He, Liu; Yang, Haoxiang; Huang, Yuchun

    2016-10-01

    Pole-like objects, including trees, lampposts and traffic signs, are indispensable part of urban infrastructure. With the advance of vehicle-based laser scanning (VLS), massive point cloud of roadside urban areas becomes applied in 3D digital city modeling. Based on the property that different pole-like objects have various canopy parts and similar trunk parts, this paper proposed the 3D part-based shape analysis to robustly extract, identify and model the pole-like objects. The proposed method includes: 3D clustering and recognition of trunks, voxel growing and part-based 3D modeling. After preprocessing, the trunk center is identified as the point that has local density peak and the largest minimum inter-cluster distance. Starting from the trunk centers, the remaining points are iteratively clustered to the same centers of their nearest point with higher density. To eliminate the noisy points, cluster border is refined by trimming boundary outliers. Then, candidate trunks are extracted based on the clustering results in three orthogonal planes by shape analysis. Voxel growing obtains the completed pole-like objects regardless of overlaying. Finally, entire trunk, branch and crown part are analyzed to obtain seven feature parameters. These parameters are utilized to model three parts respectively and get signal part-assembled 3D model. The proposed method is tested using the VLS-based point cloud of Wuhan University, China. The point cloud includes many kinds of trees, lampposts and other pole-like posters under different occlusions and overlaying. Experimental results show that the proposed method can extract the exact attributes and model the roadside pole-like objects efficiently.

  18. Sloped Terrain Segmentation for Autonomous Drive Using Sparse 3D Point Cloud

    PubMed Central

    Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Sim, Sungdae

    2014-01-01

    A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame. PMID:25093204

  19. Sloped terrain segmentation for autonomous drive using sparse 3D point cloud.

    PubMed

    Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Jeong, Young-Sik; Um, Kyhyun; Sim, Sungdae

    2014-01-01

    A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.

  20. 3-D earthquake surface displacements from differencing pre- and post-event LiDAR point clouds

    NASA Astrophysics Data System (ADS)

    Krishnan, A. K.; Nissen, E.; Arrowsmith, R.; Saripalli, S.

    2012-12-01

    The explosion in aerial LiDAR surveying along active faults across the western United States and elsewhere provides a high-resolution topographic baseline against which to compare repeat LiDAR datasets collected after future earthquakes. We present a new method for determining 3-D coseismic surface displacements and rotations by differencing pre- and post-earthquake LiDAR point clouds using an adaptation of the Iterative Closest Point (ICP) algorithm, a point set registration technique widely used in medical imaging, computer vision and graphics. There is no need for any gridding or smoothing of the LiDAR data and the method works well even with large mismatches in the density of the two point clouds. To explore the method's performance, we simulate pre- and post-event point clouds using real ("B4") LiDAR data on the southern San Andreas Fault perturbed with displacements of known magnitude. For input point clouds with ~2 points per square meter, we are able to reproduce displacements with a 50 m grid spacing and with horizontal and vertical accuracies of ~20 cm and ~4 cm. In the future, finer grids and improved precisions should be possible with higher shot densities and better survey geo-referencing. By capturing near-fault deformation in 3-D, LiDAR differencing with ICP will complement satellite-based techniques such as InSAR which map only certain components of the surface deformation and which often break down close to surface faulting or in areas of dense vegetation. It will be especially useful for mapping shallow fault slip and rupture zone deformation, helping inform paleoseismic studies and better constrain fault zone rheology. Because ICP can image rotations directly, the technique will also help resolve the detailed kinematics of distributed zones of faulting where block rotations may be common.

  1. vPresent: A cloud based 3D virtual presentation environment for interactive product customization

    NASA Astrophysics Data System (ADS)

    Nan, Xiaoming; Guo, Fei; He, Yifeng; Guan, Ling

    2013-09-01

    In modern society, many companies offer product customization services to their customers. There are two major issues in providing customized products. First, product manufacturers need to effectively present their products to the customers who may be located in any geographical area. Second, customers need to be able to provide their feedbacks on the product in real-time. However, the traditional presentation approaches cannot effectively convey sufficient information for the product or efficiently adjust product design according to customers' real-time feedbacks. In order to address these issues, we propose vPresent , a cloud based 3D virtual presentation environment, in this paper. In vPresent, the product expert can show the 3D virtual product to the remote customers and dynamically customize the product based on customers' feedbacks, while customers can provide their opinions in real time when they are viewing a vivid 3D visualization of the product. Since the proposed vPresent is a cloud based system, the customers are able to access the customized virtual products from anywhere at any time, via desktop, laptop, or even smart phone. The proposed vPresent is expected to effectively deliver 3D visual information to customers and provide an interactive design platform for the development of customized products.

  2. 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.

  3. Non-rigid registration of 3D point clouds under isometric deformation

    NASA Astrophysics Data System (ADS)

    Ge, Xuming

    2016-11-01

    An algorithm for pairwise non-rigid registration of 3D point clouds is presented in the specific context of isometric deformations. The critical step is registration of point clouds at different epochs captured from an isometric deformation surface within overlapping regions. Based on characteristics invariant under isometric deformation, a variant of the four-point congruent sets algorithm is applied to generate correspondences between two deformed point clouds, and subsequently a RANSAC framework is used to complete cluster extraction in preparation for global optimal alignment. Examples are presented and the results compared with existing approaches to demonstrate the two main contributions of the technique: a success rate for generating true correspondences of 90% and a root mean square error after final registration of 2-3 mm.

  4. 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.

  5. Influence of 3D Radiative Effects on Satellite Retrievals of Cloud Properties

    NASA Technical Reports Server (NTRS)

    Varnai, Tamas; Marshak, Alexander; Einaudi, Franco (Technical Monitor)

    2001-01-01

    When cloud properties are retrieved from satellite observations, the calculations apply 1D theory to the 3D world: they only consider vertical structures and ignore horizontal cloud variability. This presentation discusses how big the resulting errors can be in the operational retrievals of cloud optical thickness. A new technique was developed to estimate the magnitude of potential errors by analyzing the spatial patterns of visible and infrared images. The proposed technique was used to set error bars for optical depths retrieved from new MODIS measurements. Initial results indicate that the 1 km resolution retrievals are subject to abundant uncertainties. Averaging over 50 by 50 km areas reduces the errors, but does not remove them completely; even in the relatively simple case of high sun (30 degree zenith angle), about a fifth of the examined areas had biases larger than ten percent. As expected, errors increase substantially for more oblique illumination.

  6. 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

  7. Accelerating 3D radiative transfer for realistic OCO-2 cloud-aerosol scenes

    NASA Astrophysics Data System (ADS)

    Schmidt, S.; Massie, S. T.; Platnick, S. E.; Song, S.

    2014-12-01

    The recently launched NASA OCO-2 satellite is expected to provide important information about the carbon dioxide distribution in the troposphere down to Earth's surface. Among the challenges in accurately retrieving CO2 concentration from the hyperspectral observations in each of the three OCO-2 bands are cloud and aerosol impacts on the observed radiances. Preliminary studies based on idealized cloud fields have shown that they can lead to spectrally dependent radiance perturbations which differ from band to band and may lead to biases in the derived products. Since OCO-2 was inserted into the A-Train, it is only natural to capitalize on sensor synergies with other instruments, in this case on the cloud and aerosol scene context that is provided by MODIS and CALIOP. Our approach is to use cloud imagery (especially for inhomogeneous scenes) for predicting the hyperspectral observations within a collocated OCO-2 footprint and comparing with the observations, which allows a systematic assessment of the causes for biases in the retrievals themselves, and their manifestation in spectral residuals for various different cloud types and distributions. Simulating a large number of cases with line-by-line calculations using a 3D code is computationally prohibitive even on large parallel computers. Therefore, we developed a number of acceleration approaches. In this contribution, we will analyze them in terms of their speed and accuracy, using cloud fields from airborne imagery collected during a recent NASA field experiment (SEAC4RS) as proxy for different types of inhomogeneous cloud fields. The broader goal of this effort is to improve OCO-2 retrievals in the vicinity of cloud fields, and to extend the range of conditions under which the instrument will provide useful results.

  8. Quality of 3d Point Clouds from Highly Overlapping Uav Imagery

    NASA Astrophysics Data System (ADS)

    Haala, N.; Cramer, M.; Rothermel, M.

    2013-08-01

    UAVs are becoming standard platforms for photogrammetric data capture especially while aiming at large scale aerial mapping for areas of limited extent. Such applications especially benefit from the very reasonable price of a small light UAS including control system and standard consumer grade digital camera, which is some orders of magnitude lower compared to digital photogrammetric systems. Within the paper the capability of UAV-based data collection will be evaluated for two different consumer camera systems and compared to an aerial survey with a state-of-the-art digital airborne camera system. During this evaluation, the quality of 3D point clouds generated by dense multiple image matching will be used as a benchmark. Also due to recent software developments such point clouds can be generated at a resolution similar to the ground sampling distance of the available imagery and are used for an increasing number of applications. Usually, image matching benefits from the good images quality as provided from digital airborne camera systems, which is frequently not available from the low-cost sensor components used for UAV image collection. Within the paper an investigation on UAV-based 3D data capture will be presented. For this purpose dense 3D point clouds are generated for a test area from three different platforms: first a UAV with a light weight compact camera, second a system using a system camera and finally a medium-format airborne digital camera system. Despite the considerable differences in system costs, suitable results can be derived from all data, especially if large redundancy is available such highly overlapping image blocks are not only beneficial during georeferencing, but are especially advantageous while aiming at a dense and accurate image based 3D surface reconstruction.

  9. Evaluation Model for Pavement Surface Distress on 3d Point Clouds from Mobile Mapping System

    NASA Astrophysics Data System (ADS)

    Aoki, K.; Yamamoto, K.; Shimamura, H.

    2012-07-01

    This paper proposes a methodology to evaluate the pavement surface distress for maintenance planning of road pavement using 3D point clouds from Mobile Mapping System (MMS). The issue on maintenance planning of road pavement requires scheduled rehabilitation activities for damaged pavement sections to keep high level of services. The importance of this performance-based infrastructure asset management on actual inspection data is globally recognized. Inspection methodology of road pavement surface, a semi-automatic measurement system utilizing inspection vehicles for measuring surface deterioration indexes, such as cracking, rutting and IRI, have already been introduced and capable of continuously archiving the pavement performance data. However, any scheduled inspection using automatic measurement vehicle needs much cost according to the instruments' specification or inspection interval. Therefore, implementation of road maintenance work, especially for the local government, is difficult considering costeffectiveness. Based on this background, in this research, the methodologies for a simplified evaluation for pavement surface and assessment of damaged pavement section are proposed using 3D point clouds data to build urban 3D modelling. The simplified evaluation results of road surface were able to provide useful information for road administrator to find out the pavement section for a detailed examination and for an immediate repair work. In particular, the regularity of enumeration of 3D point clouds was evaluated using Chow-test and F-test model by extracting the section where the structural change of a coordinate value was remarkably achieved. Finally, the validity of the current methodology was investigated by conducting a case study dealing with the actual inspection data of the local roads.

  10. 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.

  11. Automatic co-registration of 3D multi-sensor point clouds

    NASA Astrophysics Data System (ADS)

    Persad, Ravi Ancil; Armenakis, Costas

    2017-08-01

    We propose an approach for the automatic coarse alignment of 3D point clouds which have been acquired from various platforms. The method is based on 2D keypoint matching performed on height map images of the point clouds. Initially, a multi-scale wavelet keypoint detector is applied, followed by adaptive non-maxima suppression. A scale, rotation and translation-invariant descriptor is then computed for all keypoints. The descriptor is built using the log-polar mapping of Gabor filter derivatives in combination with the so-called Rapid Transform. In the final step, source and target height map keypoint correspondences are determined using a bi-directional nearest neighbour similarity check, together with a threshold-free modified-RANSAC. Experiments with urban and non-urban scenes are presented and results show scale errors ranging from 0.01 to 0.03, 3D rotation errors in the order of 0.2° to 0.3° and 3D translation errors from 0.09 m to 1.1 m.

  12. - and Graph-Based Point Cloud Segmentation of 3d Scenes Using Perceptual Grouping Laws

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

    Segmentation is the fundamental step for recognizing and extracting objects from point clouds of 3D scene. In this paper, we present a strategy for point cloud segmentation using voxel structure and graph-based clustering with perceptual grouping laws, which allows a learning-free and completely automatic but parametric solution for segmenting 3D point cloud. To speak precisely, two segmentation methods utilizing voxel and supervoxel structures are reported and tested. The voxel-based data structure can increase efficiency and robustness of the segmentation process, suppressing the negative effect of noise, outliers, and uneven points densities. The clustering of voxels and supervoxel is carried out using graph theory on the basis of the local contextual information, which commonly conducted utilizing merely pairwise information in conventional clustering algorithms. By the use of perceptual laws, our method conducts the segmentation in a pure geometric way avoiding the use of RGB color and intensity information, so that it can be applied to more general applications. Experiments using different datasets have demonstrated that our proposed methods can achieve good results, especially for complex scenes and nonplanar surfaces of objects. Quantitative comparisons between our methods and other representative segmentation methods also confirms the effectiveness and efficiency of our proposals.

  13. 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.

  14. Automated extraction and analysis of rock discontinuity characteristics from 3D point clouds

    NASA Astrophysics Data System (ADS)

    Bianchetti, Matteo; Villa, Alberto; Agliardi, Federico; Crosta, Giovanni B.

    2016-04-01

    A reliable characterization of fractured rock masses requires an exhaustive geometrical description of discontinuities, including orientation, spacing, and size. These are required to describe discontinuum rock mass structure, perform Discrete Fracture Network and DEM modelling, or provide input for rock mass classification or equivalent continuum estimate of rock mass properties. Although several advanced methodologies have been developed in the last decades, a complete characterization of discontinuity geometry in practice is still challenging, due to scale-dependent variability of fracture patterns and difficult accessibility to large outcrops. Recent advances in remote survey techniques, such as terrestrial laser scanning and digital photogrammetry, allow a fast and accurate acquisition of dense 3D point clouds, which promoted the development of several semi-automatic approaches to extract discontinuity features. Nevertheless, these often need user supervision on algorithm parameters which can be difficult to assess. To overcome this problem, we developed an original Matlab tool, allowing fast, fully automatic extraction and analysis of discontinuity features with no requirements on point cloud accuracy, density and homogeneity. The tool consists of a set of algorithms which: (i) process raw 3D point clouds, (ii) automatically characterize discontinuity sets, (iii) identify individual discontinuity surfaces, and (iv) analyse their spacing and persistence. The tool operates in either a supervised or unsupervised mode, starting from an automatic preliminary exploration data analysis. The identification and geometrical characterization of discontinuity features is divided in steps. First, coplanar surfaces are identified in the whole point cloud using K-Nearest Neighbor and Principal Component Analysis algorithms optimized on point cloud accuracy and specified typical facet size. Then, discontinuity set orientation is calculated using Kernel Density Estimation and

  15. Parameter Estimation of Fossil Oysters from High Resolution 3D Point Cloud and Image Data

    NASA Astrophysics Data System (ADS)

    Djuricic, Ana; Harzhauser, Mathias; Dorninger, Peter; Nothegger, Clemens; Mandic, Oleg; Székely, Balázs; Molnár, Gábor; Pfeifer, Norbert

    2014-05-01

    A unique fossil oyster reef was excavated at Stetten in Lower Austria, which is also the highlight of the geo-edutainment park 'Fossilienwelt Weinviertel'. It provides the rare opportunity to study the Early Miocene flora and fauna of the Central Paratethys Sea. The site presents the world's largest fossil oyster biostrome formed about 16.5 million years ago in a tropical estuary of the Korneuburg Basin. About 15,000 up to 80-cm-long shells of Crassostrea gryphoides cover a 400 m2 large area. Our project 'Smart-Geology for the World's largest fossil oyster reef' combines methods of photogrammetry, geology and paleontology to document, evaluate and quantify the shell bed. This interdisciplinary approach will be applied to test hypotheses on the genesis of the taphocenosis (e.g.: tsunami versus major storm) and to reconstruct pre- and post-event processes. Hence, we are focusing on using visualization technologies from photogrammetry in geology and paleontology in order to develop new methods for automatic and objective evaluation of 3D point clouds. These will be studied on the basis of a very dense surface reconstruction of the oyster reef. 'Smart Geology', as extension of the classic discipline, exploits massive data, automatic interpretation, and visualization. Photogrammetry provides the tools for surface acquisition and objective, automated interpretation. We also want to stress the economic aspect of using automatic shape detection in paleontology, which saves manpower and increases efficiency during the monitoring and evaluation process. Currently, there are many well known algorithms for 3D shape detection of certain objects. We are using dense 3D laser scanning data from an instrument utilizing the phase shift measuring principle, which provides accurate geometrical basis < 3 mm. However, the situation is difficult in this multiple object scenario where more than 15,000 complete or fragmentary parts of an object with random orientation are found. The goal

  16. Grammar-Supported 3d Indoor Reconstruction from Point Clouds for As-Built Bim

    NASA Astrophysics Data System (ADS)

    Becker, S.; Peter, M.; Fritsch, D.

    2015-03-01

    The paper presents a grammar-based approach for the robust automatic reconstruction of 3D interiors from raw point clouds. The core of the approach is a 3D indoor grammar which is an extension of our previously published grammar concept for the modeling of 2D floor plans. The grammar allows for the modeling of buildings whose horizontal, continuous floors are traversed by hallways providing access to the rooms as it is the case for most office buildings or public buildings like schools, hospitals or hotels. The grammar is designed in such way that it can be embedded in an iterative automatic learning process providing a seamless transition from LOD3 to LOD4 building models. Starting from an initial low-level grammar, automatically derived from the window representations of an available LOD3 building model, hypotheses about indoor geometries can be generated. The hypothesized indoor geometries are checked against observation data - here 3D point clouds - collected in the interior of the building. The verified and accepted geometries form the basis for an automatic update of the initial grammar. By this, the knowledge content of the initial grammar is enriched, leading to a grammar with increased quality. This higher-level grammar can then be applied to predict realistic geometries to building parts where only sparse observation data are available. Thus, our approach allows for the robust generation of complete 3D indoor models whose quality can be improved continuously as soon as new observation data are fed into the grammar-based reconstruction process. The feasibility of our approach is demonstrated based on a real-world example.

  17. Distributed network, wireless and cloud computing enabled 3-D ultrasound; a new medical technology paradigm.

    PubMed

    Meir, Arie; Rubinsky, Boris

    2009-11-19

    Medical technologies are indispensable to modern medicine. However, they have become exceedingly expensive and complex and are not available to the economically disadvantaged majority of the world population in underdeveloped as well as developed parts of the world. For example, according to the World Health Organization about two thirds of the world population does not have access to medical imaging. In this paper we introduce a new medical technology paradigm centered on wireless technology and cloud computing that was designed to overcome the problems of increasing health technology costs. We demonstrate the value of the concept with an example; the design of a wireless, distributed network and central (cloud) computing enabled three-dimensional (3-D) ultrasound system. Specifically, we demonstrate the feasibility of producing a 3-D high end ultrasound scan at a central computing facility using the raw data acquired at the remote patient site with an inexpensive low end ultrasound transducer designed for 2-D, through a mobile device and wireless connection link between them. Producing high-end 3D ultrasound images with simple low-end transducers reduces the cost of imaging by orders of magnitude. It also removes the requirement of having a highly trained imaging expert at the patient site, since the need for hand-eye coordination and the ability to reconstruct a 3-D mental image from 2-D scans, which is a necessity for high quality ultrasound imaging, is eliminated. This could enable relatively untrained medical workers in developing nations to administer imaging and a more accurate diagnosis, effectively saving the lives of people.

  18. Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud

    NASA Astrophysics Data System (ADS)

    Chen, Jianqin; Zhu, Hehua; Li, Xiaojun

    2016-10-01

    This paper presents a new method for extracting discontinuity orientation automatically from rock mass surface 3D point cloud. The proposed method consists of four steps: (1) automatic grouping of discontinuity sets using an improved K-means clustering method, (2) discontinuity segmentation and optimization, (3) discontinuity plane fitting using Random Sample Consensus (RANSAC) method, and (4) coordinate transformation of discontinuity plane. The method is first validated by the point cloud of a small piece of a rock slope acquired by photogrammetry. The extracted discontinuity orientations are compared with measured ones in the field. Then it is applied to a publicly available LiDAR data of a road cut rock slope at Rockbench repository. The extracted discontinuity orientations are compared with the method proposed by Riquelme et al. (2014). The results show that the presented method is reliable and of high accuracy, and can meet the engineering needs.

  19. Multiwavelength Study to Reveal Dust Properties and Cloud 3D Structure

    NASA Astrophysics Data System (ADS)

    Pagani, Laurent; Lefevre, C.

    2017-06-01

    The study of low-mass prestellar cores is a difficult task which needs to gather several tools, dust and gas observations, radiative transfer modelling. No single tracer can reveal the physical characteristics of these cores. We show that based on observations of N2H+, and dust from 1 µm to 1 mm, one can hope today to have a faithful 3D description of a dark cloud and its prestellar core. Dust being ill-defined, only the combination of absorption, scattering and emission measurements and modelling can alleviate the degeneracy between temperature, density and emissivity of the dust.

  20. Deriving 3d Point Clouds from Terrestrial Photographs - Comparison of Different Sensors and Software

    NASA Astrophysics Data System (ADS)

    Niederheiser, Robert; Mokroš, Martin; Lange, Julia; Petschko, Helene; Prasicek, Günther; Oude Elberink, Sander

    2016-06-01

    Terrestrial photogrammetry nowadays offers a reasonably cheap, intuitive and effective approach to 3D-modelling. However, the important choice, which sensor and which software to use is not straight forward and needs consideration as the choice will have effects on the resulting 3D point cloud and its derivatives. We compare five different sensors as well as four different state-of-the-art software packages for a single application, the modelling of a vegetated rock face. The five sensors represent different resolutions, sensor sizes and price segments of the cameras. The software packages used are: (1) Agisoft PhotoScan Pro (1.16), (2) Pix4D (2.0.89), (3) a combination of Visual SFM (V0.5.22) and SURE (1.2.0.286), and (4) MicMac (1.0). We took photos of a vegetated rock face from identical positions with all sensors. Then we compared the results of the different software packages regarding the ease of the workflow, visual appeal, similarity and quality of the point cloud. While PhotoScan and Pix4D offer the user-friendliest workflows, they are also "black-box" programmes giving only little insight into their processing. Unsatisfying results may only be changed by modifying settings within a module. The combined workflow of Visual SFM, SURE and CloudCompare is just as simple but requires more user interaction. MicMac turned out to be the most challenging software as it is less user-friendly. However, MicMac offers the most possibilities to influence the processing workflow. The resulting point-clouds of PhotoScan and MicMac are the most appealing.

  1. Maps of clouds modeled with the IPSL Titan 3D-GCM

    NASA Astrophysics Data System (ADS)

    Burgalat, J.; Rannou, P.; Lebonnois, S.

    2011-10-01

    A new climate model for Titan's atmosphere has been developed at the IPSL. This model uses the current version of the LMDZ General Circulation Model (GCM) dynamical core with the physics part of the 2D Titan's IPSL-GCM. First simulations made at the LMD (Laboratoire de Météorologie Dynamique) used a version of the model with coupled haze microphysics only. We update the model with the implementation of the clouds microphysics scheme inherited frome the previous 2D version. The model is now fully coupled with clouds processes and is a full 3D extension of the Titan IPSL-GCM ([2], [3]). Currently the model is not optimized and is demanding in term of computational time (approximatively 17 days of execution for one Titan's year simulation) and the model can not be used with its full capacities. Therefore all the microphysics is still computed as zonal averages. Nevertheless, new simulations performed including clouds, shows some encouraging results. The lack of asymmetry of the clouds coverage in the results of the 2D simulations. seems to vanish using the new model which tends to show that dissipation process in the 2D model was too strong. With this new model, we intented to get a better tool to understand Titan's climate and to interpret the large amount of data collected by the probes.

  2. Maps of clouds modeled with the IPSL Titan 3D-GCM

    NASA Astrophysics Data System (ADS)

    Burgalat, J.; Rannou, P.; Lebonnois, S.

    2012-09-01

    A new climate model for Titan's atmosphere has been developed at the IPSL. This model uses the current version of the LMDZ General Circulation Model (GCM) dynamical core with the physics part of the 2D Titan's IPSL-GCM. First simulations made at the LMD (Laboratoire de Météorologie Dynamique) used a version of the model with coupled haze microphysics only. We update the model with the implementation of the clouds microphysics scheme inherited from the previous 2D version. The model is now fully coupled with clouds processes and is a full 3D extension of the Titan IPSL-GCM ([2], [3]). Currently the model is not optimized and is demanding in term of computational time (approximatively 17 days of execution for one Titan's year simulation) and the model can not be used with its full capacities. Therefore all the microphysics is still computed as zonal averages. Nevertheless, new simulations performed including clouds, shows some encouraging results. The lack of asymmetry of the clouds coverage in the results of the 2D simulations seems to vanish using the new model which tends to show that dissipation process in the 2D model was too strong. With this new model, we intented to get a better tool to understand Titan's climate and to interpret the large amount of data collected by the probes.

  3. Simulation of subgrid orographic precipitation with an embedded 2-D cloud-resolving model

    NASA Astrophysics Data System (ADS)

    Jung, Joon-Hee; Arakawa, Akio

    2016-03-01

    By explicitly resolving cloud-scale processes with embedded two-dimensional (2-D) cloud-resolving models (CRMs), superparameterized global atmospheric models have successfully simulated various atmospheric events over a wide range of time scales. Up to now, however, such models have not included the effects of topography on the CRM grid scale. We have used both 3-D and 2-D CRMs to simulate the effects of topography with prescribed "large-scale" winds. The 3-D CRM is used as a benchmark. The results show that the mean precipitation can be simulated reasonably well by using a 2-D representation of topography as long as the statistics of the topography such as the mean and standard deviation are closely represented. It is also shown that the use of a set of two perpendicular 2-D grids can significantly reduce the error due to a 2-D representation of topography.

  4. Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

    NASA Technical Reports Server (NTRS)

    Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

    2016-01-01

    Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).

  5. Observing molecular dynamics with time-resolved 3D momentum imaging

    NASA Astrophysics Data System (ADS)

    Sturm, F. P.; Wright, T.; Bocharova, I.; Ray, D.; Shivaram, N.; Cryan, J.; Belkacem, A.; Weber, T.; Dörner, R.

    2014-05-01

    Photo-excitation and ionization trigger rich dynamics in molecular systems which play a key role in many important processes in nature such as vision, photosynthesis or photoprotection. Observing those reactions in real-time without significantly disturbing the molecules by a strong electric field has been a great challenge. Recent experiments using Time-of-Flight and Velocity Map Imaging techniques have revealed important information on the dynamics of small molecular systems upon photo-excitation. We have developed an apparatus for time-resolved momentum imaging of electrons and ions in all three spatial dimensions that employs two-color femtosecond laser pulses in the vacuum and extreme ultraviolet (VUV, XUV) for probing molecular dynamics. Our COLTRIMS style reaction microscope can measure electrons and ions in coincidence and reconstruct the momenta of the reaction fragments in 3D. We use a high power 800 nm laser in a loose focusing geometry gas cell to efficinetly drive High Harmonic Generation. The resulting photon flux is sufficient to perform 2-photon pump-probe experiments using VUV and XUV pulses for both pump and probe. With this setup we investigate non-Born-Oppenheimer dynamics in small molecules such as C2H4 and CO2 on a femtosecond time scale. Supported by Chemical Sciences, Geosciences and Biosciences division of BES/DOE.

  6. 3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds

    PubMed Central

    Díaz-Vilariño, Lucía; Khoshelham, Kourosh; Martínez-Sánchez, Joaquín; Arias, Pedro

    2015-01-01

    3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction. PMID:25654723

  7. PointCloudExplore 2: Visual exploration of 3D gene expression

    SciTech Connect

    International Research Training Group Visualization of Large and Unstructured Data Sets, University of Kaiserslautern, Germany; Institute for Data Analysis and Visualization, University of California, Davis, CA; Computational Research Division, Lawrence Berkeley National Laboratory , Berkeley, CA; Genomics Division, LBNL; Computer Science Department, University of California, Irvine, CA; Computer Science Division,University of California, Berkeley, CA; Life Sciences Division, LBNL; Department of Molecular and Cellular Biology and the Center for Integrative Genomics, University of California, Berkeley, CA; Ruebel, Oliver; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Keranen, Soile V.E.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; DePace, Angela H.; Simirenko, L.; Eisen, Michael B.; Biggin, Mark D.; Hagen, Hand; Malik, Jitendra; Knowles, David W.; Hamann, Bernd

    2008-03-31

    To better understand how developmental regulatory networks are defined inthe genome sequence, the Berkeley Drosophila Transcription Network Project (BDNTP)has developed a suite of methods to describe 3D gene expression data, i.e.,the output of the network at cellular resolution for multiple time points. To allow researchersto explore these novel data sets we have developed PointCloudXplore (PCX).In PCX we have linked physical and information visualization views via the concept ofbrushing (cell selection). For each view dedicated operations for performing selectionof cells are available. In PCX, all cell selections are stored in a central managementsystem. Cells selected in one view can in this way be highlighted in any view allowingfurther cell subset properties to be determined. Complex cell queries can be definedby combining different cell selections using logical operations such as AND, OR, andNOT. Here we are going to provide an overview of PointCloudXplore 2 (PCX2), thelatest publicly available version of PCX. PCX2 has shown to be an effective tool forvisual exploration of 3D gene expression data. We discuss (i) all views available inPCX2, (ii) different strategies to perform cell selection, (iii) the basic architecture ofPCX2., and (iv) illustrate the usefulness of PCX2 using selected examples.

  8. 3D modeling of building indoor spaces and closed doors from imagery and point clouds.

    PubMed

    Díaz-Vilariño, Lucía; Khoshelham, Kourosh; Martínez-Sánchez, Joaquín; Arias, Pedro

    2015-02-03

    3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.

  9. Object recognition and localization from 3D point clouds by maximum-likelihood estimation.

    PubMed

    Dantanarayana, Harshana G; Huntley, Jonathan M

    2017-08-01

    We present an algorithm based on maximum-likelihood analysis for the automated recognition of objects, and estimation of their pose, from 3D point clouds. Surfaces segmented from depth images are used as the features, unlike 'interest point'-based algorithms which normally discard such data. Compared to the 6D Hough transform, it has negligible memory requirements, and is computationally efficient compared to iterative closest point algorithms. The same method is applicable to both the initial recognition/pose estimation problem as well as subsequent pose refinement through appropriate choice of the dispersion of the probability density functions. This single unified approach therefore avoids the usual requirement for different algorithms for these two tasks. In addition to the theoretical description, a simple 2 degrees of freedom (d.f.) example is given, followed by a full 6 d.f. analysis of 3D point cloud data from a cluttered scene acquired by a projected fringe-based scanner, which demonstrated an RMS alignment error as low as 0.3 mm.

  10. Railway Tunnel Clearance Inspection Method Based on 3D Point Cloud from Mobile Laser Scanning.

    PubMed

    Zhou, Yuhui; Wang, Shaohua; Mei, Xi; Yin, Wangling; Lin, Chunfeng; Hu, Qingwu; Mao, Qingzhou

    2017-09-07

    Railway tunnel clearance is directly related to the safe operation of trains and upgrading of freight capacity. As more and more railway are put into operation and the operation is continuously becoming faster, the railway tunnel clearance inspection should be more precise and efficient. In view of the problems existing in traditional tunnel clearance inspection methods, such as low density, slow speed and a lot of manual operations, this paper proposes a tunnel clearance inspection approach based on 3D point clouds obtained by a mobile laser scanning system (MLS). First, a dynamic coordinate system for railway tunnel clearance inspection has been proposed. A rail line extraction algorithm based on 3D linear fitting is implemented from the segmented point cloud to establish a dynamic clearance coordinate system. Second, a method to seamlessly connect all rail segments based on the railway clearance restrictions, and a seamless rail alignment is formed sequentially from the middle tunnel section to both ends. Finally, based on the rail alignment and the track clearance coordinate system, different types of clearance frames are introduced for intrusion operation with the tunnel section to realize the tunnel clearance inspection. By taking the Shuanghekou Tunnel of the Chengdu-Kunming Railway as an example, when the clearance inspection is carried out by the method mentioned herein, its precision can reach 0.03 m, and difference types of clearances can be effectively calculated. This method has a wide application prospects.

  11. Railway Tunnel Clearance Inspection Method Based on 3D Point Cloud from Mobile Laser Scanning

    PubMed Central

    Zhou, Yuhui; Wang, Shaohua; Mei, Xi; Yin, Wangling; Lin, Chunfeng; Mao, Qingzhou

    2017-01-01

    Railway tunnel clearance is directly related to the safe operation of trains and upgrading of freight capacity. As more and more railway are put into operation and the operation is continuously becoming faster, the railway tunnel clearance inspection should be more precise and efficient. In view of the problems existing in traditional tunnel clearance inspection methods, such as low density, slow speed and a lot of manual operations, this paper proposes a tunnel clearance inspection approach based on 3D point clouds obtained by a mobile laser scanning system (MLS). First, a dynamic coordinate system for railway tunnel clearance inspection has been proposed. A rail line extraction algorithm based on 3D linear fitting is implemented from the segmented point cloud to establish a dynamic clearance coordinate system. Second, a method to seamlessly connect all rail segments based on the railway clearance restrictions, and a seamless rail alignment is formed sequentially from the middle tunnel section to both ends. Finally, based on the rail alignment and the track clearance coordinate system, different types of clearance frames are introduced for intrusion operation with the tunnel section to realize the tunnel clearance inspection. By taking the Shuanghekou Tunnel of the Chengdu–Kunming Railway as an example, when the clearance inspection is carried out by the method mentioned herein, its precision can reach 0.03 m, and difference types of clearances can be effectively calculated. This method has a wide application prospects. PMID:28880232

  12. Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection

    NASA Astrophysics Data System (ADS)

    Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.

    2016-06-01

    In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

  13. 3D registration method based on scattered point cloud from B-model ultrasound image

    NASA Astrophysics Data System (ADS)

    Hu, Lei; Xu, Xiaojun; Wang, Lifeng; Guo, Na; Xie, Feng

    2017-01-01

    The paper proposes a registration method on 3D point cloud of the bone tissue surface extracted by B-mode ultrasound image and the CT model . The B-mode ultrasound is used to get two-dimensional images of the femur tissue . The binocular stereo vision tracker is used to obtain spatial position and orientation of the optical positioning device fixed on the ultrasound probe. The combining of the two kind of data generates 3D point cloud of the bone tissue surface. The pixel coordinates of the bone surface are automatically obtained from ultrasound image using an improved local phase symmetry (phase symmetry, PS) . The mapping of the pixel coordinates on the ultrasound image and 3D space is obtained through a series of calibration methods. In order to detect the effect of registration, six markers are implanted on a complete fresh pig femoral .The actual coordinates of the marks are measured with two methods. The first method is to get the coordinates with measuring tools under a coordinate system. The second is to measure the coordinates of the markers in the CT model registered with 3D point cloud using the ICP registration algorithm under the same coordinate system. Ten registration experiments are carried out in the same way. Error results are obtained by comparing the two sets of mark point coordinates obtained by two different methods. The results is that a minimum error is 1.34mm, the maximum error is 3.22mm,and the average error of 2.52mm; ICP registration algorithm calculates the average error of 0.89mm and a standard deviation of 0.62mm.This evaluation standards of registration accuracy is different from the average error obtained by the ICP registration algorithm. It can be intuitive to show the error caused by the operation of clinical doctors. Reference to the accuracy requirements of different operation in the Department of orthopedics, the method can be apply to the bone reduction and the anterior cruciate ligament surgery.

  14. PointCloudXplore: a visualization tool for 3D gene expressiondata

    SciTech Connect

    Rubel, Oliver; Weber, Gunther H.; Keranen, Soile V.E.; Fowlkes,Charles C.; Luengo Hendriks, Cristian L.; Simirenko, Lisa; Shah, NameetaY.; Eisen, Michael B.; Biggn, Mark D.; Hagen, Hans; Sudar, Damir J.; Malik, Jitendra; Knowles, David W.; Hamann, Bernd

    2006-10-01

    The Berkeley Drosophila Transcription Network Project (BDTNP) has developed a suite of methods that support quantitative, computational analysis of three-dimensional (3D) gene expression patterns with cellular resolution in early Drosophila embryos, aiming at a more in-depth understanding of gene regulatory networks. We describe a new tool, called PointCloudXplore (PCX), that supports effective 3D gene expression data exploration. PCX is a visualization tool that uses the established visualization techniques of multiple views, brushing, and linking to support the analysis of high-dimensional datasets that describe many genes' expression. Each of the views in PointCloudXplore shows a different gene expression data property. Brushing is used to select and emphasize data associated with defined subsets of embryo cells within a view. Linking is used to show in additional views the expression data for a group of cells that have first been highlighted as a brush in a single view, allowing further data subset properties to be determined. In PCX, physical views of the data are linked to abstract data displays such as parallel coordinates. Physical views show the spatial relationships between different genes' expression patterns within an embryo. Abstract gene expression data displays on the other hand allow for an analysis of relationships between different genes directly in the gene expression space. We discuss on parallel coordinates as one example abstract data view currently available in PCX. We have developed several extensions to standard parallel coordinates to facilitate brushing and the visualization of 3D gene expression data.

  15. Biview Learning for Human Posture Segmentation from 3D Points Cloud

    PubMed Central

    Qiao, Maoying; Cheng, Jun; Bian, Wei; Tao, Dacheng

    2014-01-01

    Posture segmentation plays an essential role in human motion analysis. The state-of-the-art method extracts sufficiently high-dimensional features from 3D depth images for each 3D point and learns an efficient body part classifier. However, high-dimensional features are memory-consuming and difficult to handle on large-scale training dataset. In this paper, we propose an efficient two-stage dimension reduction scheme, termed biview learning, to encode two independent views which are depth-difference features (DDF) and relative position features (RPF). Biview learning explores the complementary property of DDF and RPF, and uses two stages to learn a compact yet comprehensive low-dimensional feature space for posture segmentation. In the first stage, discriminative locality alignment (DLA) is applied to the high-dimensional DDF to learn a discriminative low-dimensional representation. In the second stage, canonical correlation analysis (CCA) is used to explore the complementary property of RPF and the dimensionality reduced DDF. Finally, we train a support vector machine (SVM) over the output of CCA. We carefully validate the effectiveness of DLA and CCA utilized in the two-stage scheme on our 3D human points cloud dataset. Experimental results show that the proposed biview learning scheme significantly outperforms the state-of-the-art method for human posture segmentation. PMID:24465721

  16. Biview learning for human posture segmentation from 3D points cloud.

    PubMed

    Qiao, Maoying; Cheng, Jun; Bian, Wei; Tao, Dacheng

    2014-01-01

    Posture segmentation plays an essential role in human motion analysis. The state-of-the-art method extracts sufficiently high-dimensional features from 3D depth images for each 3D point and learns an efficient body part classifier. However, high-dimensional features are memory-consuming and difficult to handle on large-scale training dataset. In this paper, we propose an efficient two-stage dimension reduction scheme, termed biview learning, to encode two independent views which are depth-difference features (DDF) and relative position features (RPF). Biview learning explores the complementary property of DDF and RPF, and uses two stages to learn a compact yet comprehensive low-dimensional feature space for posture segmentation. In the first stage, discriminative locality alignment (DLA) is applied to the high-dimensional DDF to learn a discriminative low-dimensional representation. In the second stage, canonical correlation analysis (CCA) is used to explore the complementary property of RPF and the dimensionality reduced DDF. Finally, we train a support vector machine (SVM) over the output of CCA. We carefully validate the effectiveness of DLA and CCA utilized in the two-stage scheme on our 3D human points cloud dataset. Experimental results show that the proposed biview learning scheme significantly outperforms the state-of-the-art method for human posture segmentation.

  17. Microphysical Timescales in Clouds and their Application in Cloud-Resolving Modeling

    NASA Technical Reports Server (NTRS)

    Zeng, Xi-Ping; Tao, Wei-Kuo; Simpson, Joanne

    2004-01-01

    Computational phenomena (i.e., spurious supersaturation and negative mixing ratio of cloud water) usually exist in cloud-resolving models when the time step for explicit integration is larger than a microphysical timescale in clouds. In this paper, the microphysical timescales in clouds are studied, showing that the timescale of water vapor condensation (or cloud water evaporation) is smaller than 10 s - the order of a typical time step for cloud-resolving models. To avoid spurious computational phenomena in cloud-resolving modeling, it is suggested that moist entropy be used as a prognostic thermodynamic variable, and temperature be diagnosed from that and other prognostic variables. A simple numerical model with moist entropy as a prognostic variable, for example, is presented to show that spurious computational phenomena are removed when moist entropy is used as a prognostic variable.

  18. Dynamic 3-D chemical agent cloud mapping using a sensor constellation deployed on mobile platforms

    NASA Astrophysics Data System (ADS)

    Cosofret, Bogdan R.; Konno, Daisei; Rossi, David; Marinelli, William J.; Seem, Pete

    2014-05-01

    The need for standoff detection technology to provide early Chem-Bio (CB) threat warning is well documented. Much of the information obtained by a single passive sensor is limited to bearing and angular extent of the threat cloud. In order to obtain absolute geo-location, range to threat, 3-D extent and detailed composition of the chemical threat, fusion of information from multiple passive sensors is needed. A capability that provides on-the-move chemical cloud characterization is key to the development of real-time Battlespace Awareness. We have developed, implemented and tested algorithms and hardware to perform the fusion of information obtained from two mobile LWIR passive hyperspectral sensors. The implementation of the capability is driven by current Nuclear, Biological and Chemical Reconnaissance Vehicle operational tactics and represents a mission focused alternative of the already demonstrated 5-sensor static Range Test Validation System (RTVS).1 The new capability consists of hardware for sensor pointing and attitude information which is made available for streaming and aggregation as part of the data fusion process for threat characterization. Cloud information is generated using 2-sensor data ingested into a suite of triangulation and tomographic reconstruction algorithms. The approaches are amenable to using a limited number of viewing projections and unfavorable sensor geometries resulting from mobile operation. In this paper we describe the system architecture and present an analysis of results obtained during the initial testing of the system at Dugway Proving Ground during BioWeek 2013.

  19. 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.

  20. Comparison of Cloud Resolving Model Simulations to Remote Sensing Data

    NASA Technical Reports Server (NTRS)

    Randall, David A.; Eitzen, Zachary

    2005-01-01

    The purpose of this research was to evaluate the ability of a cloud-resolving model (CRM) to simulate the dynamical, radiative, and microphysical properties of deep convective cloud objects identified using CERES (Clouds and the Earth s Radiant Energy System) on board the Tropical Rainfall Measuring Mission (TRMM) satellite platform, for many cases. A deep convective cloud object is a contiguous region that is composed of satellite footprints that fulfill the following selection criteria: 100% cloud fraction, cloud optical depth > 10, and a cloud top height of at least 10 km. Selection criteria have also been formed for different types of boundary-layer clouds, as described in Xu et al. (2005). The purpose of the cloud object approach is to identify specific areas of where the cloud properties simulated by the CRM systematically differ from the observed cloud properties. Where these systematic differences exist, concrete steps can be made to improve the CRM s simulation of an entire class of clouds, rather than by tuning the model to correctly simulate a single case study, as is often done. Additional information regarding detailed approaches and findings are presented.

  1. Time-resolved fuel injector flow characterisation based on 3D laser Doppler vibrometry

    NASA Astrophysics Data System (ADS)

    Crua, Cyril; Heikal, Morgan R.

    2014-12-01

    Hydrodynamic turbulence and cavitation are known to play a significant role in high-pressure atomizers, but the small geometries and extreme operating conditions hinder the understanding of the flow’s characteristics. Diesel internal flow experiments are generally conducted using x-ray techniques or on transparent, and often enlarged, nozzles with different orifice geometries and surface roughness to those found in production injectors. In order to enable investigations of the fuel flow inside unmodified injectors, we have developed a new experimental approach to measure time-resolved vibration spectra of diesel nozzles using a 3D laser vibrometer. The technique we propose is based on the triangulation of the vibrometer and fuel pressure transducer signals, and enables the quantitative characterisation of quasi-cyclic internal flows without requiring modifications to the injector, the working fluid, or limiting the fuel injection pressure. The vibrometer, which uses the Doppler effect to measure the velocity of a vibrating object, was used to scan injector nozzle tips during the injection event. The data were processed using a discrete Fourier transform to provide time-resolved spectra for valve-closed-orifice, minisac and microsac nozzle geometries, and injection pressures ranging from 60 to 160 MPa, hence offering unprecedented insight into cyclic cavitation and internal mechanical dynamic processes. A peak was consistently found in the spectrograms between 6 and 7.5 kHz for all nozzles and injection pressures. Further evidence of a similar spectral peak was obtained from the fuel pressure transducer and a needle lift sensor mounted into the injector body. Evidence of propagation of the nozzle oscillations to the liquid sprays was obtained by recording high-speed videos of the near-nozzle diesel jet, and computing the fast Fourier transform for a number of pixel locations at the interface of the jets. This 6-7.5 kHz frequency peak is proposed to be the

  2. 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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  5. LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

    NASA Astrophysics Data System (ADS)

    Amiridis, V.; Marinou, E.; Tsekeri, A.; Wandinger, U.; Schwarz, A.; Giannakaki, E.; Mamouri, R.; Kokkalis, P.; Binietoglou, I.; Solomos, S.; Herekakis, T.; Kazadzis, S.; Gerasopoulos, E.; Proestakis, E.; Kottas, M.; Balis, D.; Papayannis, A.; Kontoes, C.; Kourtidis, K.; Papagiannopoulos, N.; Mona, L.; Pappalardo, G.; Le Rille, O.; Ansmann, A.

    2015-07-01

    We present LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies), a 3-D multi-wavelength global aerosol and cloud optical database, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. The LIVAS database provides averaged profiles of aerosol optical properties for the potential spaceborne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global database is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent backscatter- and extinction-related Ångström exponents, derived from EARLINET (European Aerosol Research Lidar Network) ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversions are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO backscatter and extinction data corresponding to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud optical database based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for spaceborne lidar performance assessments. The final global data set includes 4-year (1 January 2008-31 December 2011) time-averaged CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data on a uniform grid of 1

  6. 3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

    NASA Technical Reports Server (NTRS)

    Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

    2004-01-01

    Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

  7. 3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

    NASA Technical Reports Server (NTRS)

    Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

    2004-01-01

    Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

  8. Implicit Shape Models for Object Detection in 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Velizhev, A.; Shapovalov, R.; Schindler, K.

    2012-07-01

    We present a method for automatic object localization and recognition in 3D point clouds representing outdoor urban scenes. The method is based on the implicit shape models (ISM) framework, which recognizes objects by voting for their center locations. It requires only few training examples per class, which is an important property for practical use. We also introduce and evaluate an improved version of the spin image descriptor, more robust to point density variation and uncertainty in normal direction estimation. Our experiments reveal a significant impact of these modifications on the recognition performance. We compare our results against the state-of-the-art method and get significant improvement in both precision and recall on the Ohio dataset, consisting of combined aerial and terrestrial LiDAR scans of 150,000 m2 of urban area in total.

  9. Status of the phenomena representation, 3D modeling, and cloud-based software architecture development

    SciTech Connect

    Smith, Curtis L.; Prescott, Steven; Kvarfordt, Kellie; Sampath, Ram; Larson, Katie

    2015-09-01

    Early in 2013, researchers at the Idaho National Laboratory outlined a technical framework to support the implementation of state-of-the-art probabilistic risk assessment to predict the safety performance of advanced small modular reactors. From that vision of the advanced framework for risk analysis, specific tasks have been underway in order to implement the framework. This report discusses the current development of a several tasks related to the framework implementation, including a discussion of a 3D physics engine that represents the motion of objects (including collision and debris modeling), cloud-based analysis tools such as a Bayesian-inference engine, and scenario simulations. These tasks were performed during 2015 as part of the technical work associated with the Advanced Reactor Technologies Program.

  10. An adaptive learning approach for 3-D surface reconstruction from point clouds.

    PubMed

    Junior, Agostinho de Medeiros Brito; Neto, Adrião Duarte Dória; de Melo, Jorge Dantas; Goncalves, Luiz Marcos Garcia

    2008-06-01

    In this paper, we propose a multiresolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3-D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen's self-organizing map (SOM). Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multiresolution, iterative scheme. Reconstruction was experimented on with several point sets, including different shapes and sizes. Results show generated meshes very close to object final shapes. We include measures of performance and discuss robustness.

  11. Self-Consistent 3D Modeling of Electron Cloud Dynamics and Beam Response

    SciTech Connect

    Furman, Miguel; Furman, M.A.; Celata, C.M.; Kireeff-Covo, M.; Sonnad, K.G.; Vay, J.-L.; Venturini, M.; Cohen, R.; Friedman, A.; Grote, D.; Molvik, A.; Stoltz, P.

    2007-04-02

    We present recent advances in the modeling of beam electron-cloud dynamics, including surface effects such as secondary electron emission, gas desorption, etc, and volumetric effects such as ionization of residual gas and charge-exchange reactions. Simulations for the HCX facility with the code WARP/POSINST will be described and their validity demonstrated by benchmarks against measurements. The code models a wide range of physical processes and uses a number of novel techniques, including a large-timestep electron mover that smoothly interpolates between direct orbit calculation and guiding-center drift equations, and a new computational technique, based on a Lorentz transformation to a moving frame, that allows the cost of a fully 3D simulation to be reduced to that of a quasi-static approximation.

  12. Weakly Supervised Segmentation-Aided Classification of Urban Scenes from 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Guinard, S.; Landrieu, L.

    2017-05-01

    We consider the problem of the semantic classification of 3D LiDAR point clouds obtained from urban scenes when the training set is limited. We propose a non-parametric segmentation model for urban scenes composed of anthropic objects of simple shapes, partionning the scene into geometrically-homogeneous segments which size is determined by the local complexity. This segmentation can be integrated into a conditional random field classifier (CRF) in order to capture the high-level structure of the scene. For each cluster, this allows us to aggregate the noisy predictions of a weakly-supervised classifier to produce a higher confidence data term. We demonstrate the improvement provided by our method over two publicly-available large-scale data sets.

  13. Recognizing objects in 3D point clouds with multi-scale local features.

    PubMed

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-12-15

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms.

  14. Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features

    PubMed Central

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694

  15. Geometric Features and Their Relevance for 3d Point Cloud Classification

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Jutzi, B.; Mallet, C.; Weinmann, M.

    2017-05-01

    In this paper, we focus on the automatic interpretation of 3D point cloud data in terms of associating a class label to each 3D point. While much effort has recently been spent on this research topic, little attention has been paid to the influencing factors that affect the quality of the derived classification results. For this reason, we investigate fundamental influencing factors making geometric features more or less relevant with respect to the classification task. We present a framework which consists of five components addressing point sampling, neighborhood recovery, feature extraction, classification and feature relevance assessment. To analyze the impact of the main influencing factors which are represented by the given point sampling and the selected neighborhood type, we present the results derived with different configurations of our framework for a commonly used benchmark dataset for which a reference labeling with respect to three structural classes (linear structures, planar structures and volumetric structures) as well as a reference labeling with respect to five semantic classes (Wire, Pole/Trunk, Façade, Ground and Vegetation) is available.

  16. Time-resolved 3D contrast-enhanced MRA of an extended FOV using continuous table motion.

    PubMed

    Madhuranthakam, Ananth J; Kruger, David G; Riederer, Stephen J; Glockner, James F; Hu, Houchun H

    2004-03-01

    A method is presented for acquiring 3D time-resolved MR images of an extended (>100 cm) longitudinal field of view (FOV), as used for peripheral MR angiographic runoff studies. Previous techniques for long-FOV peripheral MRA have generally provided a single image (i.e., with no time resolution). The technique presented here generates a time series of 3D images of the FOV that lies within the homogeneous volume of the magnet. This is achieved by differential sampling of 3D k-space during continuous motion of the patient table. Each point in the object is interrogated in five consecutive 3D image sets generated at 2.5-s intervals. The method was tested experimentally in eight human subjects, and the leading edge of the bolus was observed in real time and maintained within the imaging FOV. The data revealed differential bolus velocities along the vasculature of the legs.

  17. Feature-constrained surface reconstruction approach for point cloud data acquired with 3D laser scanner

    NASA Astrophysics Data System (ADS)

    Wang, Yongbo; Sheng, Yehua; Lu, Guonian; Tian, Peng; Zhang, Kai

    2008-04-01

    Surface reconstruction is an important task in the field of 3d-GIS, computer aided design and computer graphics (CAD & CG), virtual simulation and so on. Based on available incremental surface reconstruction methods, a feature-constrained surface reconstruction approach for point cloud is presented. Firstly features are extracted from point cloud under the rules of curvature extremes and minimum spanning tree. By projecting local sample points to the fitted tangent planes and using extracted features to guide and constrain the process of local triangulation and surface propagation, topological relationship among sample points can be achieved. For the constructed models, a process named consistent normal adjustment and regularization is adopted to adjust normal of each face so that the correct surface model is achieved. Experiments show that the presented approach inherits the convenient implementation and high efficiency of traditional incremental surface reconstruction method, meanwhile, it avoids improper propagation of normal across sharp edges, which means the applicability of incremental surface reconstruction is greatly improved. Above all, appropriate k-neighborhood can help to recognize un-sufficient sampled areas and boundary parts, the presented approach can be used to reconstruct both open and close surfaces without additional interference.

  18. Feature extraction from 3D lidar point clouds using image processing methods

    NASA Astrophysics Data System (ADS)

    Zhu, Ling; Shortridge, Ashton; Lusch, David; Shi, Ruoming

    2011-10-01

    Airborne LiDAR data have become cost-effective to produce at local and regional scales across the United States and internationally. These data are typically collected and processed into surface data products by contractors for state and local communities. Current algorithms for advanced processing of LiDAR point cloud data are normally implemented in specialized, expensive software that is not available for many users, and these users are therefore unable to experiment with the LiDAR point cloud data directly for extracting desired feature classes. The objective of this research is to identify and assess automated, readily implementable GIS procedures to extract features like buildings, vegetated areas, parking lots and roads from LiDAR data using standard image processing tools, as such tools are relatively mature with many effective classification methods. The final procedure adopted employs four distinct stages. First, interpolation is used to transfer the 3D points to a high-resolution raster. Raster grids of both height and intensity are generated. Second, multiple raster maps - a normalized surface model (nDSM), difference of returns, slope, and the LiDAR intensity map - are conflated to generate a multi-channel image. Third, a feature space of this image is created. Finally, supervised classification on the feature space is implemented. The approach is demonstrated in both a conceptual model and on a complex real-world case study, and its strengths and limitations are addressed.

  19. 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.

  20. Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping

    PubMed Central

    2013-01-01

    Background Laserscanning recently has become a powerful and common method for plant parameterization and plant growth observation on nearly every scale range. However, 3D measurements with high accuracy, spatial resolution and speed result in a multitude of points that require processing and analysis. The primary objective of this research has been to establish a reliable and fast technique for high throughput phenotyping using differentiation, segmentation and classification of single plants by a fully automated system. In this report, we introduce a technique for automated classification of point clouds of plants and present the applicability for plant parameterization. Results A surface feature histogram based approach from the field of robotics was adapted to close-up laserscans of plants. Local geometric point features describe class characteristics, which were used to distinguish among different plant organs. This approach has been proven and tested on several plant species. Grapevine stems and leaves were classified with an accuracy of up to 98%. The proposed method was successfully transferred to 3D-laserscans of wheat plants for yield estimation. Wheat ears were separated with an accuracy of 96% from other plant organs. Subsequently, the ear volume was calculated and correlated to the ear weight, the kernel weights and the number of kernels. Furthermore the impact of the data resolution was evaluated considering point to point distances between 0.3 and 4.0 mm with respect to the classification accuracy. Conclusion We introduced an approach using surface feature histograms for automated plant organ parameterization. Highly reliable classification results of about 96% for the separation of grapevine and wheat organs have been obtained. This approach was found to be independent of the point to point distance and applicable to multiple plant species. Its reliability, flexibility and its high order of automation make this method well suited for the demands of

  1. Astigmatic multifocus microscopy enables deep 3D super-resolved imaging

    PubMed Central

    Oudjedi, Laura; Fiche, Jean-Bernard; Abrahamsson, Sara; Mazenq, Laurent; Lecestre, Aurélie; Calmon, Pierre-François; Cerf, Aline; Nöllmann, Marcelo

    2016-01-01

    We have developed a 3D super-resolution microscopy method that enables deep imaging in cells. This technique relies on the effective combination of multifocus microscopy and astigmatic 3D single-molecule localization microscopy. We describe the optical system and the fabrication process of its key element, the multifocus grating. Then, two strategies for localizing emitters with our imaging method are presented and compared with a previously described deep 3D localization algorithm. Finally, we demonstrate the performance of the method by imaging the nuclear envelope of eukaryotic cells reaching a depth of field of ~4µm. PMID:27375935

  2. Comparison of 2d and 3d Approaches for the Alignment of Uav and LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Persad, R. A.; Armenakis, C.

    2017-08-01

    The automatic alignment of 3D point clouds acquired or generated from different sensors is a challenging problem. The objective of the alignment is to estimate the 3D similarity transformation parameters, including a global scale factor, 3 rotations and 3 translations. To do so, corresponding anchor features are required in both data sets. There are two main types of alignment: i) Coarse alignment and ii) Refined Alignment. Coarse alignment issues include lack of any prior knowledge of the respective coordinate systems for a source and target point cloud pair and the difficulty to extract and match corresponding control features (e.g., points, lines or planes) co-located on both point cloud pairs to be aligned. With the increasing use of UAVs, there is a need to automatically co-register their generated point cloud-based digital surface models with those from other data acquisition systems such as terrestrial or airborne lidar point clouds. This works presents a comparative study of two independent feature matching techniques for addressing 3D conformal point cloud alignment of UAV and lidar data in different 3D coordinate systems without any prior knowledge of the seven transformation parameters.

  3. An Evaluation of the Observational Capabilities of A Scanning 95-GHz Radar in Studying the 3D Structures of Marine Stratocumulus Clouds

    NASA Astrophysics Data System (ADS)

    Bowley, Kevin

    the radar. Well-defined streaking patterns in the drizzle field (reflectivity greater than -15 dBZ) at cloud base were concluded to be concomitant with the formation of boundary layer rolls. Sounding data for these well-defined (unbroken) rolls revealed a mean sub-cloud layer wind exceeding 3.9 ms -1, sub-cloud layer shear exceeding 7.5 x 10-3 s-1, and a majority of streaks oriented within 20° of the mean sub-cloud layer wind, satisfying many boundary layer roll criteria proposed in past studies. Attempts to reconstruct the 3D cloud liquid water content and 2D column liquid water path across the scanning radar domain using Z (Reflectivity) vs. LWC (Liquid Water Content) regressions trained using the zenith measurements were proved ineffective due to the overall extent of drizzle at Graciosa, and errors associated with sensitivity loss at range. Despite some difficulties, the SWACR satisfied ARM metrics for success by proving effective at detecting weak clouds for extended time periods across a 10 km plane, and drizzle across a 20 km range, at high spatial resolutions. Difficulties in resolving accurate vertical velocity patterns also suggest the need for an adaptive sampling strategy to most effectively remove horizontal wind components.

  4. 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

  5. Comparative analysis of video processing and 3D rendering for cloud video games using different virtualization technologies

    NASA Astrophysics Data System (ADS)

    Bada, Adedayo; Alcaraz-Calero, Jose M.; Wang, Qi; Grecos, Christos

    2014-05-01

    This paper describes a comprehensive empirical performance evaluation of 3D video processing employing the physical/virtual architecture implemented in a cloud environment. Different virtualization technologies, virtual video cards and various 3D benchmarks tools have been utilized in order to analyse the optimal performance in the context of 3D online gaming applications. This study highlights 3D video rendering performance under each type of hypervisors, and other factors including network I/O, disk I/O and memory usage. Comparisons of these factors under well-known virtual display technologies such as VNC, Spice and Virtual 3D adaptors reveal the strengths and weaknesses of the various hypervisors with respect to 3D video rendering and streaming.

  6. A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

    PubMed Central

    Liu, Wenyang; Cheung, Yam; Sabouri, Pouya; Arai, Tatsuya J.; Sawant, Amit; Ruan, Dan

    2015-01-01

    achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μrecon = − 2.7 × 10−3 mm−1, σrecon = 7.0 × 10−3 mm−1) and (μCT = − 2.5 × 10−3 mm−1, σCT = 5.3 × 10−3 mm−1), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy. PMID:26520747

  7. A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

    SciTech Connect

    Liu, Wenyang; Cheung, Yam; Sabouri, Pouya; Arai, Tatsuya J.; Sawant, Amit; Ruan, Dan

    2015-11-15

    achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μ{sub recon} = − 2.7 × 10{sup −3} mm{sup −1}, σ{sub recon} = 7.0 × 10{sup −3} mm{sup −1}) and (μ{sub CT} = − 2.5 × 10{sup −3} mm{sup −1}, σ{sub CT} = 5.3 × 10{sup −3} mm{sup −1}), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.

  8. Satellite-based 3D structure of cloud and aerosols over the Indian Monsoon region: implications for aerosol-cloud interaction

    NASA Astrophysics Data System (ADS)

    Dey, Sagnik; Sengupta, Kamalaika; Basil, George; Das, Sushant; Nidhi, Nidhi; Dash, S. K.; Sarkar, Arjya; Srivastava, Parul; Singh, Ajit; Agarwal, P.

    2012-11-01

    Accurate knowledge of vertical distributions of aerosol and cloud fields and their space-time variations are required to reduce the uncertainty in estimated climate forcing. Here, multi-sensor (both passive and active) data were used to construct the climatology of 3-D cloud and aerosol fields over the Indian monsoon region. Multilayer clouds are found to persist throughout the year, among which cumulus and stratocumulus dominate the low clouds and cirrus dominates the high clouds. A combination of passive stereo-technique (MISR) and radiometric technique (ISCPP) captures the multilayer cloud structure as revealed by active sensor CALIOP. Coexistence of low clouds throughout the year with high aerosol concentration beneath and above leads to a transition from increasing to decreasing cloud fraction with an increase in aerosol optical depth. Such transition is rapid in the monsoon season due to convergence of low clouds to form high clouds facilitated by high aerosol loading. Further, the regional climate model RegCM 4.1 has been used to examine aerosol-cloud interaction. The aerosol-induced changes of low cloud amount are under-estimated by the model. The observation-based seasonal climatology of aerosol and cloud fields presented here may help in improving the model simulations of cloud variability and associated rainfall.

  9. Architecture of web services in the enhancement of real-time 3D video virtualization in cloud environment

    NASA Astrophysics Data System (ADS)

    Bada, Adedayo; Wang, Qi; Alcaraz-Calero, Jose M.; Grecos, Christos

    2016-04-01

    This paper proposes a new approach to improving the application of 3D video rendering and streaming by jointly exploring and optimizing both cloud-based virtualization and web-based delivery. The proposed web service architecture firstly establishes a software virtualization layer based on QEMU (Quick Emulator), an open-source virtualization software that has been able to virtualize system components except for 3D rendering, which is still in its infancy. The architecture then explores the cloud environment to boost the speed of the rendering at the QEMU software virtualization layer. The capabilities and inherent limitations of Virgil 3D, which is one of the most advanced 3D virtual Graphics Processing Unit (GPU) available, are analyzed through benchmarking experiments and integrated into the architecture to further speed up the rendering. Experimental results are reported and analyzed to demonstrate the benefits of the proposed approach.

  10. X-ray phase nanotomography resolves the 3D human bone ultrastructure.

    PubMed

    Langer, Max; Pacureanu, Alexandra; Suhonen, Heikki; Grimal, Quentin; Cloetens, Peter; Peyrin, Françoise

    2012-01-01

    Bone strength and failure are increasingly thought to be due to ultrastructural properties, such as the morphology of the lacuno-canalicular network, the collagen fiber orientation and the mineralization on the nanoscale. However, these properties have not been studied in 3D so far. Here we report the investigation of the human bone ultrastructure with X-ray phase nanotomography, which now provides the required sensitivity, spatial resolution and field of view. The 3D organization of the lacuno-canalicular network is studied in detail over several cells in osteonal and interstitial tissue. Nanoscale density variations are revealed and show that the cement line separating these tissues is hypermineralized. Finally, we show that the collagen fibers are organized as a twisted plywood structure in 3D.

  11. Knowledge guided object detection and identification in 3D point clouds

    NASA Astrophysics Data System (ADS)

    Karmacharya, A.; Boochs, F.; Tietz, B.

    2015-05-01

    Modern instruments like laser scanner and 3D cameras or image based techniques like structure from motion produce huge point clouds as base for further object analysis. This has considerably changed the way of data compilation away from selective manually guided processes towards automatic and computer supported strategies. However it's still a long way to achieve the quality and robustness of manual processes as data sets are mostly very complex. Looking at existing strategies 3D data processing for object detections and reconstruction rely heavily on either data driven or model driven approaches. These approaches come with their limitation on depending highly on the nature of data and inability to handle any deviation. Furthermore, the lack of capabilities to integrate other data or information in between the processing steps further exposes their limitations. This restricts the approaches to be executed with strict predefined strategy and does not allow deviations when and if new unexpected situations arise. We propose a solution that induces intelligence in the processing activities through the usage of semantics. The solution binds the objects along with other related knowledge domains to the numerical processing to facilitate the detection of geometries and then uses experts' inference rules to annotate them. The solution was tested within the prototypical application of the research project "Wissensbasierte Detektion von Objekten in Punktwolken für Anwendungen im Ingenieurbereich (WiDOP)". The flexibility of the solution is demonstrated through two entirely different USE Case scenarios: Deutsche Bahn (German Railway System) for the outdoor scenarios and Fraport (Frankfort Airport) for the indoor scenarios. Apart from the difference in their environments, they provide different conditions, which the solution needs to consider. While locations of the objects in Fraport were previously known, that of DB were not known at the beginning.

  12. Processing 3D flash LADAR point-clouds in real-time for flight applications

    NASA Astrophysics Data System (ADS)

    Craig, R.; Gravseth, I.; Earhart, R. P.; Bladt, J.; Barnhill, S.; Ruppert, L.; Centamore, C.

    2007-04-01

    Ball Aerospace & Technologies Corp. has demonstrated real-time processing of 3D imaging LADAR point-cloud data to produce the industry's first time-of-flight (TOF) 3D video capability. This capability is uniquely suited to the rigorous demands of space and airborne flight applications and holds great promise in the area of autonomous navigation. It will provide long-range, three dimensional video information to autonomous flight software or pilots for immediate use in rendezvous and docking, proximity operations, landing, surface vision systems, and automatic target recognition and tracking. This is enabled by our new generation of FPGA based "pixel-tube" processors, coprocessors and their associated algorithms which have led to a number of advancements in high-speed wavefront processing along with additional advances in dynamic camera control, and space laser designs based on Ball's CALIPSO LIDAR. This evolution in LADAR is made possible by moving the mechanical complexity required for a scanning system into the electronics, where production, integration, testing and life-cycle costs can be significantly reduced. This technique requires a state of the art TOF read-out integrated circuit (ROIC) attached to a sensor array to collect high resolution temporal data, which is then processed through FPGAs. The number of calculations required to process the data is greatly reduced thanks to the fact that all points are captured at the same time and thus correlated. This correlation allows extremely efficient FPGA processing. This capability has been demonstrated in prototype form at both Marshal Space Flight Center and Langley Research Center on targets that represent docking and landing scenarios. This report outlines many aspects of this work as well as aspects of our recent testing at Marshall's Flight Robotics Laboratory.

  13. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  14. A cloud-resolving model study of aerosol-cloud correlation in a pristine maritime environment

    NASA Astrophysics Data System (ADS)

    Nishant, Nidhi; Sherwood, Steven C.

    2017-06-01

    In convective clouds, satellite-observed deepening or increased amount of clouds with increasing aerosol concentration has been reported and is sometimes interpreted as aerosol-induced invigoration of the clouds. However, such correlations can be affected by meteorological factors that affect both aerosol and clouds, as well as observational issues. In this study, we examine the behavior in a 660 × 660 km2 region of the South Pacific during June 2007, previously found by Koren et al. (2014) to show strong correlation between cloud fraction, cloud top pressure, and aerosols, using a cloud-resolving model with meteorological boundary conditions specified from a reanalysis. The model assumes constant aerosol loading, yet reproduces vigorous clouds at times of high real-world aerosol concentrations. Days with high- and low-aerosol loading exhibit deep-convective and shallow clouds, respectively, in both observations and the simulation. Synoptic analysis shows that vigorous clouds occur at times of strong surface troughs, which are associated with high winds and advection of boundary layer air from the Southern Ocean where sea-salt aerosol is abundant, thus accounting for the high correlation. Our model results show that aerosol-cloud relationships can be explained by coexisting but independent wind-aerosol and wind-cloud relationships and that no cloud condensation nuclei effect is required.

  15. Use of the ARM Measurement of Spectral Zenith Radiance For Better Understanding Of 3D Cloud-Radiation Processes and Aerosol-Cloud Interaction

    SciTech Connect

    Chiu, Jui-Yuan

    2010-10-19

    Our proposal focuses on cloud-radiation processes in a general 3D cloud situation, with particular emphasis on cloud optical depth and effective particle size. We also focus on zenith radiance measurements, both active and passive. The proposal has three main parts. Part One exploits the "solar-background" mode of ARM lidars to allow them to retrieve cloud optical depth not just for thin clouds but for all clouds. This also enables the study of aerosol cloud interactions with a single instrument. Part Two exploits the large number of new wavelengths offered by ARM's zenith-pointing ShortWave Spectrometer (SWS), especially during CLASIC, to develop better retrievals not only of cloud optical depth but also of cloud particle size. We also propose to take advantage of the SWS's 1 Hz sampling to study the "twilight zone" around clouds where strong aerosol-cloud interactions are taking place. Part Three involves continuing our cloud optical depth and cloud fraction retrieval research with ARM's 2NFOV instrument by, first, analyzing its data from the AMF-COPS/CLOWD deployment, and second, making our algorithms part of ARM's operational data processing.

  16. Time-resolved UV-visible spectroelectrochemistry using transparent 3D-mesoporous nanocrystalline ITO electrodes.

    PubMed

    Renault, Christophe; Harris, Kenneth D; Brett, Michael J; Balland, Véronique; Limoges, Benoît

    2011-02-14

    Efficient and rapid adsorption of microperoxidase 11 within a highly porous ITO thin film (200 nm) prepared by glancing angle deposition was achieved. Adsorbed redox molecules were reversibly and rapidly reduced throughout the 3D-conductive matrix in ca. 50 ms, allowing the heterogeneous electron transfer rate to be determined by derivative cyclic voltabsorptometry.

  17. Cloud 3D Effects Evidenced in Landsat Power Spectra and Autocorrelation Functions

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    the spectral signatures of decorrelation between reflectance and optical depth at large scales becoming stronger as the magnitude of cloud top variations increase. Finally, the usefulness of power spectral analysis in evaluating the skill of novel optical depth retrieval techniques in removing 3D radiative effects is demonstrated. New techniques using inverse Non-local Independent Pixel Approximation (NIPA) and Normalized Difference of Nadir Reflectivity (NDNR) yield optical depth fields which better match the scale-by-scale variability of the true optical depth field.

  18. CAST: Effective and Efficient User Interaction for Context-Aware Selection in 3D Particle Clouds.

    PubMed

    Yu, Lingyun; Efstathiou, Konstantinos; Isenberg, Petra; Isenberg, Tobias

    2016-01-01

    We present a family of three interactive Context-Aware Selection Techniques (CAST) for the analysis of large 3D particle datasets. For these datasets, spatial selection is an essential prerequisite to many other analysis tasks. Traditionally, such interactive target selection has been particularly challenging when the data subsets of interest were implicitly defined in the form of complicated structures of thousands of particles. Our new techniques SpaceCast, TraceCast, and PointCast improve usability and speed of spatial selection in point clouds through novel context-aware algorithms. They are able to infer a user's subtle selection intention from gestural input, can deal with complex situations such as partially occluded point clusters or multiple cluster layers, and can all be fine-tuned after the selection interaction has been completed. Together, they provide an effective and efficient tool set for the fast exploratory analysis of large datasets. In addition to presenting Cast, we report on a formal user study that compares our new techniques not only to each other but also to existing state-of-the-art selection methods. Our results show that Cast family members are virtually always faster than existing methods without tradeoffs in accuracy. In addition, qualitative feedback shows that PointCast and TraceCast were strongly favored by our participants for intuitiveness and efficiency.

  19. 3-D numerical simulations of eruption clouds: Effects of the environmental wind on the turbulent mixing

    NASA Astrophysics Data System (ADS)

    Suzuki, Y. J.; Koyaguchi, T.

    2011-12-01

    During an explosive volcanic eruption, a mixture of volcanic gas and solid pyroclasts are ejected from a volcanic vent with a high temperature. As it rises, the mixture entrains ambient air owing to turbulent mixing. The entrained air expands by heating from the hot pyroclasts, and the eruption cloud (i.e., the ejected material plus the entrained air) rises as a buoyant plume. Because the plume height is principally determined by the balance between the thermal energy ejected at the vent and the work done in transporting the ejected material plus entrained air through the atmospheric stratification, it is controlled by the efficiency of turbulent mixing; as the amount of entrained air increases, the plume height decreases. In the 1-D models of eruption column (e.g., Woods, 1988), the plume height is calculated on the assumption that the mean inflow velocity across the edge of turbulent jet and/or plume is proportional to the mean vertical velocity (Morton et al., 1956). Experimental studies suggest that the proportionality constant (i.e., entrainment coefficient, k), which represents the efficiency of turbulent mixing, is about 0.10 for pure plumes when there is no wind. When an environmental wind is present, however, the interaction between a buoyant plume and the wind may enhance the entrainment of air and can significantly decrease the plume height (Bursik, 2001). In order to investigate the effects of wind on the vortical structures and the efficiency of turbulent mixing in an eruption cloud, we have carried out 3-D numerical simulations of eruption column which is ejected in a wind field. The simulation results indicate that a buoyant plume vertically rises as a "strong plume" (e.g., Bonadonna et al., 2003) when the wind velocity is low: the cloud reaches the neutral buoyancy level and overshoots until the upward momentum is exhausted. In this case, the plume height is consistent with prediction by the 1-D model with k~0.10. When the wind velocity is high, on

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Remote sensing is a key tool for sorting cloud ensembles by dynamical state, aerosol environments by source region, and establishing causal relationships between aerosol amounts, type, and cloud microphysics-the so-called indirect aerosol climate impacts, and one of the main sources of uncertainty in current climate models. Current satellite imagers use data processing approaches that invariably start with cloud detection/masking to isolate aerosol air-masses from clouds, and then rely on one-dimensional (1D) radiative transfer (RT) to interpret the aerosol and cloud measurements in isolation. Not only does this lead to well-documented biases for the estimates of aerosol radiative forcing and cloud optical depths in current missions, but it is fundamentally inadequate for future missions such as EarthCARE where capturing the complex, three-dimensional (3D) interactions between clouds and aerosols is a primary objective. In order to advance the state of the art, the next generation of satellite information processing systems must incorporate technologies that will enable the treatment of the atmosphere as a fully 3D environment, represented more realistically as a continuum. At one end, there is an optically thin background dominated by aerosols and molecular scattering that is strongly stratified and relatively homogeneous in the horizontal. At the other end, there are optically thick embedded elements, clouds and aerosol plumes, which can be more or less uniform and quasi-planar or else highly 3D with boundaries in all directions; in both cases, strong internal variability may be present. To make this paradigm shift possible, we propose to combine the standard models for satellite signal prediction physically grounded in 1D and 3D RT, both scalar and vector, with technologies adapted from biomedical imaging, digital image processing, and computer vision. This will enable us to demonstrate how the 3D distribution of atmospheric constituents, and their associated

  1. Representing 3-D cloud radiation effects in two-stream schemes: 2. Matrix formulation and broadband evaluation

    NASA Astrophysics Data System (ADS)

    Hogan, Robin J.; Schäfer, Sophia A. K.; Klinger, Carolin; Chiu, J. Christine; Mayer, Bernhard

    2016-07-01

    Estimating the impact of radiation transport through cloud sides on the global energy budget is hampered by the lack of a fast radiation scheme suitable for use in global atmospheric models that can represent these effects in both the shortwave and longwave. This two-part paper describes the development of such a scheme, which we refer to as the Speedy Algorithm for Radiative Transfer through Cloud Sides (SPARTACUS). The principle of the method is to add extra terms to the two-stream equations to represent lateral transport between clear and cloudy regions, which vary in proportion to the length of cloud edge as a function of height. The present paper describes a robust and accurate method for solving the coupled system of equations in both the shortwave and longwave in terms of matrix exponentials. This solver has been coupled to a correlated-k model for gas absorption. We then confirm the accuracy of SPARTACUS by performing broadband comparisons with fully 3-D radiation calculations by the Monte Carlo model "MYSTIC" for a cumulus cloud field, examining particularly the percentage change in cloud radiative effect (CRE) when 3-D effects are introduced. In the shortwave, SPARTACUS correctly captures this change to CRE, which varies with solar zenith angle between -25% and +120%. In the longwave, SPARTACUS captures well the increase in radiative cooling of the cloud, although it is only able to correctly simulate the 30% increase in surface CRE (around 4 W m-2) if an approximate correction is made for cloud clustering.

  2. Validating Air Force Weather Satellite Retrieved 3D Cloud Products against Independent Ground and Space-Based Assets

    NASA Astrophysics Data System (ADS)

    Nobis, T. E.; Conner, M. D.

    2016-12-01

    Air Force Weather (AFW) has documented requirements for global cloud analyses and forecasts to support DoD missions around the world. Cloud analyses are constructed using passive cloud detection algorithms from 17 different near real time satellite sources. The algorithms are run on individual satellite transmissions at native satellite resolution in near real time. These native resolution products are then used to construct an hourly global merge on a 24km grid. AFW has also recently started creation of a time-delayed global cloud reanalysis to produce a `best possible' analysis for climatology and verification purposes. Cloud forecasts include global short-range cloud forecasts created using advection techniques as well as statistically post-processed cloud forecast products derived from various global and regional numerical weather forecast models. The result is a mix of cloud products covering different spatial and temporal resolutions with varying latency requirements. AFW has started to aggressively benchmark the performance of their current capabilities. Cloud information collected from so called `active' sensors on the ground at the DOE-ARM sites and from space by such instruments as CloudSat, CALIPSO and CATS are being utilized to characterize the performance of AFW products derived largely by passive means. The goal is to understand the performance of the 3D cloud analysis and forecast products of today to help shape the requirements and standards for a future Numerical Weather Model driven cloud analysis and forecast system driven by advanced 4DVAR techniques. This presentation will present selected results from these benchmarking efforts and highlight insights and observations between passively and actively derived observations and the impacts of varying spatial and temporal depictions of clouds.

  3. Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Fang, Lina; Li, Jonathan

    2013-05-01

    Accurate 3D road information is important for applications such as road maintenance and virtual 3D modeling. Mobile laser scanning (MLS) is an efficient technique for capturing dense point clouds that can be used to construct detailed road models for large areas. This paper presents a method for extracting and delineating roads from large-scale MLS point clouds. The proposed method partitions MLS point clouds into a set of consecutive "scanning lines", which each consists of a road cross section. A moving window operator is used to filter out non-ground points line by line, and curb points are detected based on curb patterns. The detected curb points are tracked and refined so that they are both globally consistent and locally similar. To evaluate the validity of the proposed method, experiments were conducted using two types of street-scene point clouds captured by Optech's Lynx Mobile Mapper System. The completeness, correctness, and quality of the extracted roads are over 94.42%, 91.13%, and 91.3%, respectively, which proves the proposed method is a promising solution for extracting 3D roads from MLS point clouds.

  4. Low cost digital photogrammetry: From the extraction of point clouds by SFM technique to 3D mathematical modeling

    NASA Astrophysics Data System (ADS)

    Michele, Mangiameli; Giuseppe, Mussumeci; Salvatore, Zito

    2017-07-01

    The Structure From Motion (SFM) is a technique applied to a series of photographs of an object that returns a 3D reconstruction made up by points in the space (point clouds). This research aims at comparing the results of the SFM approach with the results of a 3D laser scanning in terms of density and accuracy of the model. The experience was conducted by detecting several architectural elements (walls and portals of historical buildings) both with a 3D laser scanner of the latest generation and an amateur photographic camera. The point clouds acquired by laser scanner and those acquired by the photo camera have been systematically compared. In particular we present the experience carried out on the "Don Diego Pappalardo Palace" site in Pedara (Catania, Sicily).

  5. 3D Cloud Tomography, Followed by Mean Optical and Microphysical Properties, with Multi-Angle/Multi-Pixel Data

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    The geometrical assumption in all operational cloud remote sensing algorithms is that clouds are plane-parallel slabs, which applies relatively well to the most uniform stratus layers. Its benefit is to justify using classic 1D radiative transfer (RT) theory, where angular details (solar, viewing, azimuthal) are fully accounted for and precise phase functions can be used, to generate the look-up tables used in the retrievals. Unsurprisingly, these algorithms catastrophically fail when applied to cumulus-type clouds, which are highly 3D. This is unfortunate for the cloud-process modeling community that may thrive on in situ airborne data, but would very much like to use satellite data for more than illustrations in their presentations and publications. So, how can we obtain quantitative information from space-based observations of finite aspect ratio clouds? Cloud base/top heights, vertically projected area, mean liquid water content (LWC), and volume-averaged droplet size would be a good start. Motivated by this science need, we present a new approach suitable for sparse cumulus fields where we turn the tables on the standard procedure in cloud remote sensing. We make no a priori assumption about cloud shape, save an approximately flat base, but use brutal approximations about the RT that is necessarily 3D. Indeed, the first order of business is to roughly determine the cloud's outer shape in one of two ways, which we will frame as competing initial guesses for the next phase of shape refinement and volume-averaged microphysical parameter estimation. Both steps use multi-pixel/multi-angle techniques amenable to MISR data, the latter adding a bi-spectral dimension using collocated MODIS data. One approach to rough cloud shape determination is to fit the multi-pixel/multi-angle data with a geometric primitive such as a scalene hemi-ellipsoid with 7 parameters (translation in 3D space, 3 semi-axes, 1 azimuthal orientation); for the radiometry, a simple radiosity

  6. What can Cloud-Resolving Models Tell us About Critical Phenomena in Atmospheric Precipitation?

    NASA Astrophysics Data System (ADS)

    Krueger, S. K.; Kochanski, A. K.

    2009-05-01

    Recent work suggests that observations of tropical precipitation conform to properties associated with critical phenomena of other systems (Peters and Neelin 2006). The measurements are averages over 25-km by 25- km areas and are snapshots in time, and therefore unable to reveal the underlying, smaller-scale physical processes. We are using a 3D cloud-resolving model (CRM) to resolve these processes in space and time, and thereby allow us to investigate the underlying physics in detail. The model is being run over a large domain (1000 km by 1000 km) for a long time (many days) in order to adequately sample the rare events. In addition, we are using results from a global climate model that is based on the multi-scale modeling framework (MMF). Whereas conventional parameterizations are based on statistical theories involving uncertain closure assumptions, MMFs represent cloud processes on their native scales, by embedding a 2D CRM with a 4-km horizontal grid size in each climate model grid column. We are analyzing the model results following the methodology of Peters and Neelin. We are using MMF results to produce rainfall rates conditioned on column water vapor and column temperature over the Tropical oceans. We are doing the same with 3D CRM results. Furthermore, we are comparing 2D and 3D CRM results and examining the impact of CRM horizontal grid size. We are also analyzing additional statistical aspects of Tropical convection in the 3D CRM simulations that are related to critical behavior, such as size distributions and other geometric properties of mesoscale convective systems, identified as clusters of adjacent pixels exceeding a precipitation threshold. And to evaluate the realism of the statistical properties of deep convection simulated by the 3D CRM, we are comparing its vertical velocity statistics and rainfall rate PDFs to observations from aircraft and precipitation radars, respectively.

  7. Time resolved 3D momentum imaging of ultrafast dynamics by coherent VUV-XUV radiation

    NASA Astrophysics Data System (ADS)

    Sturm, F. P.; Wright, T. W.; Ray, D.; Zalyubovskaya, I.; Shivaram, N.; Slaughter, D. S.; Ranitovic, P.; Belkacem, A.; Weber, Th.

    2016-06-01

    We present a new experimental setup for measuring ultrafast nuclear and electron dynamics of molecules after photo-excitation and ionization. We combine a high flux femtosecond vacuum ultraviolet (VUV) and extreme ultraviolet (XUV) source with an internally cold molecular beam and a 3D momentum imaging particle spectrometer to measure electrons and ions in coincidence. We describe a variety of tools developed to perform pump-probe studies in the VUV-XUV spectrum and to modify and characterize the photon beam. First benchmark experiments are presented to demonstrate the capabilities of the system.

  8. Time resolved 3D momentum imaging of ultrafast dynamics by coherent VUV-XUV radiation.

    PubMed

    Sturm, F P; Wright, T W; Ray, D; Zalyubovskaya, I; Shivaram, N; Slaughter, D S; Ranitovic, P; Belkacem, A; Weber, Th

    2016-06-01

    We present a new experimental setup for measuring ultrafast nuclear and electron dynamics of molecules after photo-excitation and ionization. We combine a high flux femtosecond vacuum ultraviolet (VUV) and extreme ultraviolet (XUV) source with an internally cold molecular beam and a 3D momentum imaging particle spectrometer to measure electrons and ions in coincidence. We describe a variety of tools developed to perform pump-probe studies in the VUV-XUV spectrum and to modify and characterize the photon beam. First benchmark experiments are presented to demonstrate the capabilities of the system.

  9. Time resolved 3D momentum imaging of ultrafast dynamics by coherent VUV-XUV radiation

    SciTech Connect

    Sturm, F. P.; Wright, T. W.; Ray, D.; Zalyubovskaya, I.; Shivaram, N.; Slaughter, D. S.; Ranitovic, P.; Belkacem, A.; Weber, Th.

    2016-06-14

    Have we present a new experimental setup for measuring ultrafast nuclear and electron dynamics of molecules after photo-excitation and ionization. We combine a high flux femtosecond vacuum ultraviolet (VUV) and extreme ultraviolet (XUV) source with an internally cold molecular beam and a 3D momentum imaging particle spectrometer to measure electrons and ions in coincidence. We describe a variety of tools developed to perform pump-probe studies in the VUV-XUV spectrum and to modify and characterize the photon beam. First benchmark experiments are presented to demonstrate the capabilities of the system.

  10. Evaluation of a 3D point cloud tetrahedral tomographic reconstruction method

    PubMed Central

    Pereira, N F; Sitek, A

    2011-01-01

    Tomographic reconstruction on an irregular grid may be superior to reconstruction on a regular grid. This is achieved through an appropriate choice of the image space model, the selection of an optimal set of points and the use of any available prior information during the reconstruction process. Accordingly, a number of reconstruction-related parameters must be optimized for best performance. In this work, a 3D point cloud tetrahedral mesh reconstruction method is evaluated for quantitative tasks. A linear image model is employed to obtain the reconstruction system matrix and five point generation strategies are studied. The evaluation is performed using the recovery coefficient, as well as voxel- and template-based estimates of bias and variance measures, computed over specific regions in the reconstructed image. A similar analysis is performed for regular grid reconstructions that use voxel basis functions. The maximum likelihood expectation maximization reconstruction algorithm is used. For the tetrahedral reconstructions, of the five point generation methods that are evaluated, three use image priors. For evaluation purposes, an object consisting of overlapping spheres with varying activity is simulated. The exact parallel projection data of this object are obtained analytically using a parallel projector, and multiple Poisson noise realizations of these exact data are generated and reconstructed using the different point generation strategies. The unconstrained nature of point placement in some of the irregular mesh-based reconstruction strategies has superior activity recovery for small, low-contrast image regions. The results show that, with an appropriately generated set of mesh points, the irregular grid reconstruction methods can out-perform reconstructions on a regular grid for mathematical phantoms, in terms of the performance measures evaluated. PMID:20736496

  11. Structured illumination multimodal 3D-resolved quantitative phase and fluorescence sub-diffraction microscopy

    PubMed Central

    Chowdhury, Shwetadwip; Eldridge, Will J.; Wax, Adam; Izatt, Joseph A.

    2017-01-01

    Sub-diffraction resolution imaging has played a pivotal role in biological research by visualizing key, but previously unresolvable, sub-cellular structures. Unfortunately, applications of far-field sub-diffraction resolution are currently divided between fluorescent and coherent-diffraction regimes, and a multimodal sub-diffraction technique that bridges this gap has not yet been demonstrated. Here we report that structured illumination (SI) allows multimodal sub-diffraction imaging of both coherent quantitative-phase (QP) and fluorescence. Due to SI’s conventionally fluorescent applications, we first demonstrate the principle of SI-enabled three-dimensional (3D) QP sub-diffraction imaging with calibration microspheres. Image analysis confirmed enhanced lateral and axial resolutions over diffraction-limited QP imaging, and established striking parallels between coherent SI and conventional optical diffraction tomography. We next introduce an optical system utilizing SI to achieve 3D sub-diffraction, multimodal QP/fluorescent visualization of A549 biological cells fluorescently tagged for F-actin. Our results suggest that SI has a unique utility in studying biological phenomena with significant molecular, biophysical, and biochemical components. PMID:28663887

  12. Reactor safety issues resolved by the 2D/3D Program. International Agreement Report

    SciTech Connect

    Damerell, P.S.; Simons, J.W.

    1993-07-01

    The 2D/3D Program studied multidimensional thermal-hydraulics in a PWR core and primary system during the end-of-blowdown and post-blowdown phases of a large-break LOCA (LBLOCA), and during selected small-break LOCA (SBLOCA) transients. The program included tests at the Cylindrical Core Test Facility (CCTF), the Slab Core Test Facility (SCTF), and the Upper Plenum Test Facility (UPTF), and computer analyses using TRAC. Tests at CCTF investigated core thermal-hydraulics and overall system behavior while tests at SCTF concentrated on multidimensional core thermal-hydraulics. The UPTF tests investigated two-phase flow behavior in the downcomer, upper plenum, tie plate region, and primary loops. TRAC analyses evaluated thermal-hydraulic behavior throughout the primary system in tests as well as in PWRs. This report summarizes the test and analysis results in each of the main areas where improved information was obtained in the 2D/3D Program. The discussion is organized in terms of the reactor safety issues investigated.

  13. Development of a 3D rockfall simulation model for point cloud topography

    NASA Astrophysics Data System (ADS)

    Noël, François; Wyser, Emmanuel; Jaboyedoff, Michel; Clouthier, Catherine; Locat, Jacques

    2017-04-01

    Rockfall simulations are generally used, for example, as input data to generate rockfall susceptibility map, to evaluate the reach probability of an infrastructure or to define input parameter values for mitigation designs. During the simulations, the lateral and vertical deviations of the particle and the change of velocity happening during the impacts have to be evaluated. Numerous factors control rockfall paths and velocities, like the particle's and terrain's shapes and compositions. Some models, especially the ones using discrete element methods, can consider a lot of physical factors. However, a compromise often has to be done between the time needed to produce a sufficient amount of 2D or 3D rockfall trajectories and the level of complexity of the model. In this presentation, the current version of our rockfall model in development is detailed and the compromises that were made are explained. For example, it is hard to predict the sizes and shapes of the components that could fall from a developing rock instability, or if they will break after the first impact or stay as massive blocks. For this reason, we decided for now to simplify the particle's shape to a sphere which can vary in size and to use a cubical shape to compute the 3D rotational inertia. In contrast to the particle's characteristics, the terrain's shape is known and can be acquired in detail using current topographical acquisition methods, e.g. airborne and terrestrial laser scans and aerial based structure from motion. We made no sacrifice on that side and developed our model so it can simulate rockfalls directly on 3D point clouds topographical data. It is also been shown that calibrating velocity weighting factors, often called restitution coefficients, is not an easy task. Divergent results could be obtained by different users using the same simulation program simply because they use different weighting factors, which are hard to evaluate and quantify from field work. Moreover, the normal

  14. Numerical simulations of altocumulus with a cloud resolving model

    SciTech Connect

    Liu, S.; Krueger, S.K.

    1996-04-01

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

  15. CloudSat Takes a 3D Slice of Hurricane Matthew

    NASA Image and Video Library

    2016-10-07

    NASA's CloudSat flew east of Hurricane Matthew's center on Oct. 6 at 11:30 a.m. PDT (2:30 p.m. EDT), intersecting parts of Matthew's outer rain bands and revealing Matthew's anvil clouds (thick cirrus cloud cover), with cumulus and cumulonimbus clouds beneath (lower image). Reds/pinks are larger water/ice droplets. http://photojournal.jpl.nasa.gov/catalog/PIA21095

  16. Anisotropy-resolving models for predicting separation in 3--D asymmetric diffusers

    NASA Astrophysics Data System (ADS)

    Jeyapaul, Elbert; Durbin, Paul

    2011-11-01

    All linear eddy-viscosity models are qualitatively incorrect in predicting separation in 3-D asymmetric diffusers. The failure to predict normal stress and shear stress anisotropy at high production-dissipation ratios is the cause. The Explicit algebraic Reynolds stress model (Wallin and Johansson, 2000) predicts the mean flow field in the diffuser accurately, but not the wall pressure and Reynolds stresses. Recalibrating the coefficients of the rapid part of pressure-strain model improves the wall pressure prediction. Including the convective, diffusive, streamline curvature effects on anisotropy has not been beneficial. The model has been tested using a family of diffusers having the same nominal streamwise pressure gradient, LES data is used as a reference. Professor

  17. Blood velocity assessment using 3D bright-blood time-resolved magnetic resonance angiography.

    PubMed

    Miraux, Sylvain; Franconi, Jean-Michel; Thiaudière, Eric

    2006-09-01

    Blood velocity is a functional parameter that is not easily assessed noninvasively, especially in small animals. A new noninvasive method that uses magnetic resonance angiography (MRA) to measure blood flows is proposed. This method is based on the time-of-flight (TOF) phenomenon. By initially suppressing the signal from the stationary spins in the area of interest, it is possible to sequentially visualize only the signal from the moving spins entering a given volume. With this method, 3D cine images of the blood flow can be generated by positive contrast, with unparalleled spatial (<200 microm) and temporal resolutions (<10 ms/image). As a result, it is possible to measure flow in sinuous paths. The present method was applied in vivo to measure the blood velocity in mouse carotid arteries. Because of its robustness and simplicity of implementation, this method has numerous potential applications for fundamental studies in small animal models. Copyright (c) 2006 Wiley-Liss, Inc.

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

    PubMed Central

    Wang, Yunsheng; Weinacker, Holger; Koch, Barbara

    2008-01-01

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

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

    PubMed

    Wang, Yunsheng; Weinacker, Holger; Koch, Barbara

    2008-06-12

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

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

    NASA Image and Video Library

    2017-09-08

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

  1. Cloud-System Resolving Models: Status and Prospects

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Moncreiff, Mitch

    2008-01-01

    Cloud-system resolving models (CRM), which are based on the nonhydrostatic equations of motion and typically have a grid-spacing of about a kilometer, originated as cloud-process models in the 1970s. This paper reviews the status and prospects of CRMs across a wide range of issues, such as microphysics and precipitation; interaction between clouds and radiation; and the effects of boundary-layer and surface-processes on cloud systems. Since CRMs resolve organized convection, tropical waves and the large-scale circulation, there is the prospect for several advances in both basic knowledge of scale-interaction requisite to parameterizing mesoscale processes in climate models. In superparameterization, CRMs represent convection, explicitly replacing many of the assumptions necessary in contemporary parameterization. Global CRMs have been run on an experimental basis, giving prospect to a new generation of climate weather prediction in a decade, and climate models due course. CRMs play a major role in the retrieval of surface-rain and latent heating from satellite measurements. Finally, enormous wide dynamic ranges of CRM simulations present new challenges for model validation against observations.

  2. Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media

    NASA Technical Reports Server (NTRS)

    Alfano, Robert R. (Inventor); Cai, Wei (Inventor); Liu, Feng (Inventor); Lax, Melvin (Inventor); Das, Bidyut B. (Inventor)

    1999-01-01

    A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: ##EQU1## wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j =/<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absoption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.

  3. Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media

    NASA Technical Reports Server (NTRS)

    Alfano, Robert R. (Inventor); Cai, Wei (Inventor); Gayen, Swapan K. (Inventor)

    2000-01-01

    A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j =/<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absorption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.

  4. A 2D-3D strategy for resolving tsunami-generated debris flow in urban environments

    NASA Astrophysics Data System (ADS)

    Birjukovs Canelas, Ricardo; Conde, Daniel; Garcia-Feal, Orlando; João Telhado, Maria; Ferreira, Rui M. L.

    2017-04-01

    The incorporation of solids, either sediment from the natural environment or remains from buildings or infrastructures is a relevant feature of tsunami run-up in urban environments, greatly increasing the destructive potential of tsunami propagation. Two-dimensional (2D) models have been used to assess the propagation of the bore, even in dense urban fronts. Computational advances are introduced in this work, namely a fully lagrangian, 3D description of the fluid-solid flow, coupled with a high performance meshless implementation capable of dealing with large domains and fine discretizations. A Smoothed Particle Hydrodynamics (SPH) Navier-Stokes discretization and a Distributed Contact Discrete Element Method (DCDEM) description of solid-solid interactions provide a state-of the-art fluid-solid flow description. Together with support for arbitrary geometries, centimetre scale resolution simulations of a city section in Lisbon downtown are presented. 2D results are used as boundary conditions for the 3D model, characterizing the incoming wave as it approaches the coast. It is shown that the incoming bore is able to mobilize and incorporate standing vehicles and other urban hardware. Such fully featured simulation provides explicit description of the interactions among fluid, floating debris (vehicles and urban furniture), the buildings and the pavement. The proposed model presents both an innovative research tool for the study of these flows and a powerful and robust approach to study, design and test mitigation solutions at the local scale. At the same time, due to the high time and space resolution of these methodologies, new questions are raised: scenario-building and initial configurations play a crucial role but they do not univocally determine the final configuration of the simulation, as the solution of the Navier-Stokes equations for high Reynolds numbers possesses a high number of degrees of freedom. This calls for conducting the simulations in a

  5. Testing remote sensing on artificial observations: impact of drizzle and 3-D cloud structure on effective radius retrievals

    NASA Astrophysics Data System (ADS)

    Zinner, T.; Wind, G.; Platnick, S.; Ackerman, A. S.

    2010-10-01

    Remote sensing of cloud effective particle size with passive sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave and midwave infrared channels. In practice, retrieved effective radii from these combinations can be quite different. This difference is perhaps indicative of different penetration depths and path lengths for the spectral reflectances used. In addition, operational liquid water cloud retrievals are based on the assumption of a relatively narrow distribution of droplet sizes; the role of larger precipitation particles in these distributions is neglected. Therefore, possible explanations for the discrepancy in some MODIS spectral size retrievals could include 3-D radiative transport effects, including sub-pixel cloud inhomogeneity, and/or the impact of drizzle formation. For three cloud cases the possible factors of influence are isolated and investigated in detail by the use of simulated cloud scenes and synthetic satellite data: marine boundary layer cloud scenes from large eddy simulations (LES) with detailed microphysics are combined with Monte Carlo radiative transfer calculations that explicitly account for the detailed droplet size distributions as well as 3-D radiative transfer to simulate MODIS observations. The operational MODIS optical thickness and effective radius retrieval algorithm is applied to these and the results are compared to the given LES microphysics. We investigate two types of marine cloud situations each with and without drizzle from LES simulations: (1) a typical daytime stratocumulus deck at two times in the diurnal cycle and (2) one scene with scattered cumulus. Only small impact of drizzle formation on the retrieved domain average and on the differences between the three effective radius retrievals is noticed

  6. Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations

    DOE PAGES

    Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas

    2015-11-05

    In this paper, we evaluate high-level clouds in a cloud resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of cloud occurrence and radar reflectivity compare well with cloud radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level cloud and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level cloud. For ARM9707, persistent large positive biases in high-level cloud are found, which are not sensitivemore » to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level cloud amount, radiation, and high sensitivity of cloud amount to nudging time scale in both convective cases. The high sensitivity of high-level cloud amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful ‘‘tuning’’ parameter for the simulated cloud and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in cloud and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level clouds in super-parameterized global climate models such as the multiscale modeling framework.« less

  7. Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations

    NASA Astrophysics Data System (ADS)

    Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas

    2015-12-01

    In this study, we evaluate high-level clouds in a cloud resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of cloud occurrence and radar reflectivity compare well with cloud radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level cloud and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level cloud. For ARM9707, persistent large positive biases in high-level cloud are found, which are not sensitive to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level cloud amount, radiation, and high sensitivity of cloud amount to nudging time scale in both convective cases. The high sensitivity of high-level cloud amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful "tuning" parameter for the simulated cloud and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in cloud and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level clouds in super-parameterized global climate models such as the multiscale modeling framework.

  8. Fast Segmentation of Stained Nuclei in Terabyte-Scale, Time Resolved 3D Microscopy Image Stacks

    PubMed Central

    Stegmaier, Johannes; Otte, Jens C.; Kobitski, Andrei; Bartschat, Andreas; Garcia, Ariel; Nienhaus, G. Ulrich; Strähle, Uwe; Mikut, Ralf

    2014-01-01

    Automated analysis of multi-dimensional microscopy images has become an integral part of modern research in life science. Most available algorithms that provide sufficient segmentation quality, however, are infeasible for a large amount of data due to their high complexity. In this contribution we present a fast parallelized segmentation method that is especially suited for the extraction of stained nuclei from microscopy images, e.g., of developing zebrafish embryos. The idea is to transform the input image based on gradient and normal directions in the proximity of detected seed points such that it can be handled by straightforward global thresholding like Otsu’s method. We evaluate the quality of the obtained segmentation results on a set of real and simulated benchmark images in 2D and 3D and show the algorithm’s superior performance compared to other state-of-the-art algorithms. We achieve an up to ten-fold decrease in processing times, allowing us to process large data sets while still providing reasonable segmentation results. PMID:24587204

  9. Depth-resolved 3D visualization of coronary microvasculature with optical microangiography

    NASA Astrophysics Data System (ADS)

    Qin, Wan; Roberts, Meredith A.; Qi, Xiaoli; Murry, Charles E.; Zheng, Ying; Wang, Ruikang K.

    2016-11-01

    In this study, we propose a novel implementation of optical coherence tomography-based angiography combined with ex vivo perfusion of fixed hearts to visualize coronary microvascular structure and function. The extracorporeal perfusion of Intralipid solution allows depth-resolved angiographic imaging, control of perfusion pressure, and high-resolution optical microangiography. The imaging technique offers new opportunities for microcirculation research in the heart, which has been challenging due to motion artifacts and the lack of independent control of pressure and flow. With the ability to precisely quantify structural and functional features, this imaging platform has broad potential for the study of the pathophysiology of microvasculature in the heart as well as other organs.

  10. Microphysical Timescales in Clouds and their Application in Cloud-Resolving Modeling

    NASA Technical Reports Server (NTRS)

    Zeng, Xiping; Tao, Wei-Kuo; Simpson, Joanne

    2007-01-01

    Independent prognostic variables in cloud-resolving modeling are chosen on the basis of the analysis of microphysical timescales in clouds versus a time step for numerical integration. Two of them are the moist entropy and the total mixing ratio of airborne water with no contributions from precipitating particles. As a result, temperature can be diagnosed easily from those prognostic variables, and cloud microphysics be separated (or modularized) from moist thermodynamics. Numerical comparison experiments show that those prognostic variables can work well while a large time step (e.g., 10 s) is used for numerical integration.

  11. Patient-individualized boundary conditions for CFD simulations using time-resolved 3D angiography.

    PubMed

    Boegel, Marco; Gehrisch, Sonja; Redel, Thomas; Rohkohl, Christopher; Hoelter, Philip; Doerfler, Arnd; Maier, Andreas; Kowarschik, Markus

    2016-06-01

    Hemodynamic simulations are of increasing interest for the assessment of aneurysmal rupture risk and treatment planning. Achievement of accurate simulation results requires the usage of several patient-individual boundary conditions, such as a geometric model of the vasculature but also individualized inflow conditions. We propose the automatic estimation of various parameters for boundary conditions for computational fluid dynamics (CFD) based on a single 3D rotational angiography scan, also showing contrast agent inflow. First the data are reconstructed, and a patient-specific vessel model can be generated in the usual way. For this work, we optimize the inflow waveform based on two parameters, the mean velocity and pulsatility. We use statistical analysis of the measurable velocity distribution in the vessel segment to estimate the mean velocity. An iterative optimization scheme based on CFD and virtual angiography is utilized to estimate the inflow pulsatility. Furthermore, we present methods to automatically determine the heart rate and synchronize the inflow waveform to the patient's heart beat, based on time-intensity curves extracted from the rotational angiogram. This will result in a patient-individualized inflow velocity curve. The proposed methods were evaluated on two clinical datasets. Based on the vascular geometries, synthetic rotational angiography data was generated to allow a quantitative validation of our approach against ground truth data. We observed an average error of approximately [Formula: see text] for the mean velocity, [Formula: see text] for the pulsatility. The heart rate was estimated very precisely with an average error of about [Formula: see text], which corresponds to about 6 ms error for the duration of one cardiac cycle. Furthermore, a qualitative comparison of measured time-intensity curves from the real data and patient-specific simulated ones shows an excellent match. The presented methods have the potential to accurately

  12. A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

    PubMed

    Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

    2014-03-01

    As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

  13. Multiple Uses of a 3d Point Cloud: the Castle of Franchimont (province of LIÈGE, Belgium)

    NASA Astrophysics Data System (ADS)

    Luczfalvy Jancsó, A.; Jonlet, B.; Hallot, P.; Hoffsummer, P.; Billen, R.

    2017-08-01

    This paper presents the identified obstacles, needs and selected solutions for the study of the medieval castle of Franchimont, located in the province of Liège (Belgium). After taking into account the requirements from all the disciplines at work as well as the problems that would have to be tackled, the creation of a 3D point cloud was decided. This solution would be able to deal with the characteristics and needs of a research involving building archaeology and related fields. The decision was made in order to manage all of the available data and to provide a common working tool for every involved cultural heritage actor. To achieve this, the elaboration of an Archaeological Information System based on 3D point clouds as a common virtual workspace is being taken into consideration.

  14. On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Zeng, Xiping; Tao, Wei-Kuo; Lang, Stephen; Hou, Arthur Y.; Zhang, Minghua; Simpson, Joanne

    2008-01-01

    Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.

  15. On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Zeng, Xiping; Tao, Wei-Kuo; Lang, Stephen; Hou, Arthur Y.; Zhang, Minghua; Simpson, Joanne

    2008-01-01

    Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.

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

    DOE PAGES

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

    2017-05-08

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-06-01

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

  18. High resolution spin- and angle-resolved photoelectron spectroscopy for 3D spin vectorial analysis

    NASA Astrophysics Data System (ADS)

    Okuda, Taichi; Miyamoto, Koji; Kimura, Akio; Namatame, Hirofumi; Taniguchi, Masaki

    2013-03-01

    Spin- and angle-resolved photoelectron spectroscopy (SARPES) is the excellent tool which can directly observe the band structure of crystals with separating spin-up and -down states. Recent findings of new class of materials possessing strong spin orbit interaction such as Rashba spin splitting systems or topological insulators stimulate to develop new SARPES apparatuses and many sophisticated techniques have been reported recently. Here we report our newly developed a SARPES apparatus for spin vectorial analysis with high precision at Hiroshima Synchrotron Radiation Center. Highly efficient spin polarimeter utilizing very low energy electron diffraction (VLEED) makes high resolution (ΔE < 10 meV, Δθ ~ +/- 0.2 °) compatible with the SARPES measurement. By placing two VLEED spin detectors orthogonally we have realized the polarization measurement of all spin components (x, y and z) with the high resolution. Some examples of the three-dimensional spin observation will be presented. This work is supported by KAKENHI (23244066), Grant-in-Aid for Scientific Research (A) of Japan Society for the Promotion of Science.

  19. Time-resolved (kHz) 3D imaging of OH PLIF in a flame

    NASA Astrophysics Data System (ADS)

    Wellander, Rikard; Richter, Mattias; Aldén, Marcus

    2014-06-01

    Based on scanning planar laser-induced fluorescence of OH, a measurement system with the capability to record time-resolved three-dimensional image sequences of the OH concentration and the flame front is demonstrated on a premixed flame. A dual-mirror scanning system is used to obtain equidistance between the illuminated planes. Non-uniformities in the laser sheet and laser absorption in the flame are compensated for as the position- and time-dependent OH concentration is calculated throughout the measurement volume. A method for identifying the flame front in large data sets with a single set of filtering parameter is demonstrated. The artefacts introduced by the non-instantaneous recording of the measurement volume are suppressed using linear interpolation from successive recordings in the same measurement plane. The impact from filtering and image post-processing on the achieved spatial resolution is investigated. A final spatial and temporal resolution of 3.2 × 3.2 × 0.75 lines/mm and 2 ms, respectively, are obtained in a measurement volume spanning 11 × 22 × 6 mm during a time span of 0.5 s.

  20. 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

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

    SciTech Connect

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

    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 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

  2. 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

  3. 3D AMR simulations of the evolution of the diffuse gas cloud G2 in the Galactic Centre

    NASA Astrophysics Data System (ADS)

    Schartmann, M.; Ballone, A.; Burkert, A.; Gillessen, S.; Genzel, R.; Pfuhl, O.; Eisenhauer, F.; Plewa, P. M.; Ott, T.; George, E. M.; Habibi, M.

    2017-01-01

    With the help of 3D AMR hydrodynamical simulations we aim at understanding G2's nature, recent evolution and fate in the coming years. By exploring the possible parameter space of the diffuse cloud scenario, we find that a starting point within the disc of young stars is favoured by the observations, which may hint at G2 being the result of stellar wind interactions.

  4. 3D granulometry: grain-scale shape and size distribution from point cloud dataset of river environments

    NASA Astrophysics Data System (ADS)

    Steer, Philippe; Lague, Dimitri; Gourdon, Aurélie; Croissant, Thomas; Crave, Alain

    2016-04-01

    The grain-scale morphology of river sediments and their size distribution are important factors controlling the efficiency of fluvial erosion and transport. In turn, constraining the spatial evolution of these two metrics offer deep insights on the dynamics of river erosion and sediment transport from hillslopes to the sea. However, the size distribution of river sediments is generally assessed using statistically-biased field measurements and determining the grain-scale shape of river sediments remains a real challenge in geomorphology. Here we determine, with new methodological approaches based on the segmentation and geomorphological fitting of 3D point cloud dataset, the size distribution and grain-scale shape of sediments located in river environments. Point cloud segmentation is performed using either machine-learning algorithms or geometrical criterion, such as local plan fitting or curvature analysis. Once the grains are individualized into several sub-clouds, each grain-scale morphology is determined using a 3D geometrical fitting algorithm applied on the sub-cloud. If different geometrical models can be conceived and tested, only ellipsoidal models were used in this study. A phase of results checking is then performed to remove grains showing a best-fitting model with a low level of confidence. The main benefits of this automatic method are that it provides 1) an un-biased estimate of grain-size distribution on a large range of scales, from centimeter to tens of meters; 2) access to a very large number of data, only limited by the number of grains in the point-cloud dataset; 3) access to the 3D morphology of grains, in turn allowing to develop new metrics characterizing the size and shape of grains. The main limit of this method is that it is only able to detect grains with a characteristic size greater than the resolution of the point cloud. This new 3D granulometric method is then applied to river terraces both in the Poerua catchment in New-Zealand and

  5. Interactive Classification of Construction Materials: Feedback Driven Framework for Annotation and Analysis of 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Hess, M. R.; Petrovic, V.; Kuester, F.

    2017-08-01

    Digital documentation of cultural heritage structures is increasingly more common through the application of different imaging techniques. Many works have focused on the application of laser scanning and photogrammetry techniques for the acquisition of threedimensional (3D) geometry detailing cultural heritage sites and structures. With an abundance of these 3D data assets, there must be a digital environment where these data can be visualized and analyzed. Presented here is a feedback driven visualization framework that seamlessly enables interactive exploration and manipulation of massive point cloud data. The focus of this work is on the classification of different building materials with the goal of building more accurate as-built information models of historical structures. User defined functions have been tested within the interactive point cloud visualization framework to evaluate automated and semi-automated classification of 3D point data. These functions include decisions based on observed color, laser intensity, normal vector or local surface geometry. Multiple case studies are presented here to demonstrate the flexibility and utility of the presented point cloud visualization framework to achieve classification objectives.

  6. Virgo cluster and field dwarf ellipticals in 3D - III. Spatially and temporally resolved stellar populations

    NASA Astrophysics Data System (ADS)

    Ryś, Agnieszka; Koleva, Mina; Falcón-Barroso, Jesús; Vazdekis, Alexandre; Lisker, Thorsten; Peletier, Reynier; van de Ven, Glenn

    2015-09-01

    We present the stellar population analysis of a sample of 12 dwarf elliptical galaxies, observed with the SAURON integral field unit, using the full-spectrum fitting method. We show that star formation histories (SFHs) resolved into two populations can be recovered even within a limited wavelength range, provided that high signal-to-noise ratio (S/N) data are used. We confirm that dEs have had complex SFHs, with star formation extending to (more) recent epochs: for the majority of our galaxies star formation activity was either still strong a few (≲5) Gyr ago or they experienced a secondary burst of star formation roughly at that time. This latter possibility is in agreement with the proposed dE formation scenario where tidal harassment drives the gas remaining in their progenitors inwards and induces a star formation episode. For one of our field galaxies, ID 0918, we find a correlation between its stellar population and kinematic properties, pointing to a possible merger origin of its kinematically decoupled core. One of our cluster objects, VCC 1431, appears to be composed exclusively of an old population (≳10-12 Gyr). Combining this with our earlier dynamical results, we conclude that the galaxy was either ram-pressure stripped early on in its evolution in a group environment and subsequently tidally heated, or that it evolved in situ in the cluster's central parts, compact enough to avoid tidal disruption. These are only two of the examples illustrating the SFH richness of these objects confirmed with our data.

  7. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE PAGES

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

    2015-06-23

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

  8. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

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

  9. Three-dimensional turbulence-resolving modeling of the Venusian cloud layer and associated gravity waves

    NASA Astrophysics Data System (ADS)

    Lefevre, Maxence; Spiga, Aymeric; Lebonnois, Sebastien

    2016-10-01

    One of the main questions that remains unclear about the dynamics of the atmosphere of Venus and its interaction with the photochemistry is the characterization of the cloud convective layer which mixes momentum, heat, chemical species and generates gravity waves observed by Venus Express. This dynamical forcing induced by the cloud layer has been proposed as a significant contribution to the maintenance of the super-rotation. However these waves develop from regional to local scales and can not be resolved by global circulation models (GCM) developed insofar. Therefore we developed an unprecedented 3D Venusian mesoscale model based on the Martian mesoscale model using the Weather Research and Forecast terrestrial model. We report the first application of this model : simulating convection in the Venusian cloud layer and associated gravity waves by 3D turbulent-resolving simulations (Large-Eddy Simulations). The model employs an offline radiative forcing based on heating rates extracted from the LMD Venus GCM consisting of three distinct kind of rates. Two radiative ones for short wave (solar) and long wave (IR) and one for the adiabatic cooling/warming due to the global dynamics of the atmosphere (mainly the Hadley cell) with 2 different cloud models. Therefore we are able to characterize the convection and associated gravity waves in function of latitude and local time. To assess the impact of the general circulation on the convection we ran simulations with forcing from a 1D radiative model.The resolved convective layer takes place between 1.0 105 and 3.8 104 Pa with vertical wind between ± 3 m/s, is organized as polygonal closed cells of about 8x8km2, and emits gravity waves on either side with temperature perturbations of about 0.5 K with vertical wavelength of 1 km and horizontal wavelength from 1 to almost 20 km. The order of magnitude of the resolved plumes is consistent with observations though underestimated.We are working on coupling the model with a

  10. 3D Modeling of interactions between Jupiter’s ammonia clouds and large anticyclones

    NASA Astrophysics Data System (ADS)

    Palotai, Csaba; Dowling, Timothy E.; Fletcher, Leigh N.

    2014-04-01

    The motions of Jupiter’s tropospheric jets and vortices are made visible by its outermost clouds, which are expected to be largely composed of ammonia ice. Several groups have demonstrated that much of this dynamics can be reproduced in the vorticity fields of high-resolution models that, surprisingly, do not contain any clouds. While this reductionist approach is valuable, it has natural limitations. Here we report on numerical simulations that use the EPIC Jupiter model with a realistic ammonia-cloud microphysics module, focusing on how observable ammonia clouds interact with the Great Red Spot (GRS) and Oval BA. Maps of column-integrated ammonia-cloud density in the model resemble visible-band images of Jupiter and potential-vorticity maps. On the other hand, vertical cross sections through the model vortices reveal considerable heterogeneity in cloud density values between pressure levels in the vicinity of large anticyclones, and interestingly, ammonia snow appears occasionally. Away from the vortices, the ammonia clouds form at the levels expected from traditional one-dimensional models, and inside the vortices, the clouds are elevated and thick, in agreement with Galileo NIMS observations. However, rather than gathering slowly into place as a result of Jupiter’s weak secondary circulation, the ammonia clouds instead form high and thick inside the large anticyclones as soon as the cloud microphysics module is enabled. This suggests that any weak secondary circulation that might be present in Jupiter’s anticyclones, such as may arise because of radiative damping of their temperature anomalies, may have little or no direct effect on the altitude or thickness of the ammonia clouds. Instead, clouds form at those locations because the top halves of large anticyclones must be cool for the vortex to be able to fit under the tropopause, which is a primary-circulation, thermal-wind-shear effect of the stratification, not a secondary-circulation thermal feature

  11. AstroCloud: An Agile platform for data visualization and specific analyzes in 2D and 3D

    NASA Astrophysics Data System (ADS)

    Molina, F. Z.; Salgado, R.; Bergel, A.; Infante, A.

    2017-07-01

    Nowadays, astronomers commonly run their own tools, or distributed computational packages, for data analysis and then visualizing the results with generic applications. This chain of processes comes at high cost: (a) analyses are manually applied, they are therefore difficult to be automatized, and (b) data have to be serialized, thus increasing the cost of parsing and saving intermediary data. We are developing AstroCloud, an agile visualization multipurpose platform intended for specific analyses of astronomical images (https://astrocloudy.wordpress.com). This platform incorporates domain-specific languages which make it easily extensible. AstroCloud supports customized plug-ins, which translate into time reduction on data analysis. Moreover, it also supports 2D and 3D rendering, including interactive features in real time. AstroCloud is under development, we are currently implementing different choices for data reduction and physical analyzes.

  12. 3-D model simulations of dynamical and microphysical interactions in pyroconvective clouds under idealized conditions

    NASA Astrophysics Data System (ADS)

    Reutter, P.; Trentmann, J.; Seifert, A.; Neis, P.; Su, H.; Chang, D.; Herzog, M.; Wernli, H.; Andreae, M. O.; Pöschl, U.

    2014-07-01

    Dynamical and microphysical processes in pyroconvective clouds in mid-latitude conditions are investigated using idealized three-dimensional simulations with the Active Tracer High resolution Atmospheric Model (ATHAM). A state-of-the-art two-moment microphysical scheme building upon a realistic parameterization of cloud condensation nuclei (CCN) activation has been implemented in order to study the influence of aerosol concentration on cloud development. The results show that aerosol concentration influences the formation of precipitation. For low aerosol concentrations (NCN = 200 cm-3), rain droplets are rapidly formed by autoconversion of cloud droplets. This also triggers the formation of large graupel and hail particles, resulting in an early onset of precipitation. With increasing aerosol concentration (NCN = 1000 cm-3 and NCN = 20 000 cm-3) the formation of rain droplets is delayed due to more but smaller cloud droplets. Therefore, the formation of ice crystals and snowflakes becomes more important for the eventual formation of graupel and hail, which is delayed at higher aerosol concentrations. This results in a delay of the onset of precipitation and a reduction of its intensity with increasing aerosol concentration. This study is the first detailed investigation of the interaction between cloud microphysics and the dynamics of a pyroconvective cloud using the combination of a high-resolution atmospheric model and a detailed microphysical scheme.

  13. NASA's CloudSat Sees Tropical Storm Harvey in 3D

    NASA Image and Video Library

    2017-08-29

    Click on the image for larger animation NASA's CloudSat satellite flew over then-Tropical Storm Harvey on Aug. 26, 2017, at 2:45 p.m. CDT (19:45 UTC) as the storm was nearly stationary over south Texas. At that time, Harvey contained estimated maximum sustained winds of 69 miles per hour (60 knots). CloudSat flew over Harvey northeast of the storm center through an area of moderate to heavy rainfall in the outer rainbands. As seen in the image and animation, large amounts of liquid and ice water (denoted by the red and pink colors) are visible beneath the cloud tops. The lack of a radar signal (attenuation) beneath the melting layer (located around 3 miles, or 5 kilometers, above ground) can be seen in the heavier areas of precipitation, since CloudSat's cloud profiling radar (CPR) signal dampens when precipitation particles are larger than 0.12 inches (3 millimeters) in size. Smaller cumulus and cumulonimbus clouds are seen north of the area of moderate to heavy precipitation. The cirrus canopy (anvil clouds) extends outward from the storm system (shown in blue and green colors). An animation is available at https://photojournal.jpl.nasa.gov/catalog/PIA17392

  14. Attribute-based point cloud visualization in support of 3-D classification

    NASA Astrophysics Data System (ADS)

    Zlinszky, András; Otepka, Johannes; Kania, Adam

    2016-04-01

    Despite the rich information available in LIDAR point attributes through full waveform recording, radiometric calibration and advanced texture metrics, LIDAR-based classification is mostly done in the raster domain. Point-based analyses such as noise removal or terrain filtering are often carried out without visual investigation of the point cloud attributes used. This is because point cloud visualization software usually handle only a limited number of pre-defined point attributes and only allow colorizing the point cloud with one of these at a time. Meanwhile, point cloud classification is rapidly evolving, and uses not only the individual attributes but combinations of these. In order to understand input data and output results better, more advanced methods for visualization are needed. Here we propose an algorithm of the OPALS software package that handles visualization of the point cloud together with its attributes. The algorithm is based on the .odm (OPALS data manager) file format that efficiently handles a large number of pre-defined point attributes and also allows the user to generate new ones. Attributes of interest can be visualized individually, by applying predefined or user-generated palettes in a simple .xml format. The colours of the palette are assigned to the points by setting the respective Red, Green and Blue attributes of the point to result in the colour pre-defined by the palette for the corresponding attribute value. The algorithm handles scaling and histogram equalization based on the distribution of the point attribute to be considered. Additionally, combinations of attributes can be visualized based on RBG colour mixing. The output dataset can be in any standard format where RGB attributes are supported and visualized with conventional point cloud viewing software. Viewing the point cloud together with its attributes allows efficient selection of filter settings and classification parameters. For already classified point clouds, a large

  15. 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.

  16. Modeling the Decay in AN Hbim Starting from 3d Point Clouds. a Followed Approach for Cultural Heritage Knowledge

    NASA Astrophysics Data System (ADS)

    Chiabrando, F.; Lo Turco, M.; Rinaudo, F.

    2017-08-01

    The recent trends in architectural data management imply the scientific and professional collaborations of several disciplines involved in the design, restoration and maintenance. It seems an achieved concept that, in the next future, all the information connected to new interventions or conservation activities on historical buildings will be managed by using a BIM platform. Nowadays the actual range or image based metric survey techniques (mainly produced by using Terrestrial Laser Scanner or photogrammetric platform today more based on projective geometry) allow to generate 3D point clouds, 3D models, orthophotos and other outputs with assessed accuracy. The subsequent conversion of 3D information into parametric components, especially in an historical environment, is not easy and has a lot of open issues. According to the actual BIM commercial software and to the embedded tools or plugin, the paper deals with the methodology followed for the realization of two parametric 3D models (Palazzo Sarmatoris and Smistamento RoundHouse, two historical building in the north-west part of Italy). The paper describes the proposed workflow according to the employed plug-in for automatic reconstruction and to the solution adopted for the well-known problems connected to the modeling phase such as the vaults realization or the 3D irregular surfaces modeling. Finally, the studied strategy for mapping the decay in a BIM environment and the connected results with the conclusions and future perspectives are critically discussed.

  17. Evaluating the Potential of Rtk-Uav for Automatic Point Cloud Generation in 3d Rapid Mapping

    NASA Astrophysics Data System (ADS)

    Fazeli, H.; Samadzadegan, F.; Dadrasjavan, F.

    2016-06-01

    During disaster and emergency situations, 3D geospatial data can provide essential information for decision support systems. The utilization of geospatial data using digital surface models as a basic reference is mandatory to provide accurate quick emergency response in so called rapid mapping activities. The recipe between accuracy requirements and time restriction is considered critical in this situations. UAVs as alternative platforms for 3D point cloud acquisition offer potentials because of their flexibility and practicability combined with low cost implementations. Moreover, the high resolution data collected from UAV platforms have the capabilities to provide a quick overview of the disaster area. The target of this paper is to experiment and to evaluate a low-cost system for generation of point clouds using imagery collected from a low altitude small autonomous UAV equipped with customized single frequency RTK module. The customized multi-rotor platform is used in this study. Moreover, electronic hardware is used to simplify user interaction with the UAV as RTK-GPS/Camera synchronization, and beside the synchronization, lever arm calibration is done. The platform is equipped with a Sony NEX-5N, 16.1-megapixel camera as imaging sensor. The lens attached to camera is ZEISS optics, prime lens with F1.8 maximum aperture and 24 mm focal length to deliver outstanding images. All necessary calibrations are performed and flight is implemented over the area of interest at flight height of 120 m above the ground level resulted in 2.38 cm GSD. Earlier to image acquisition, 12 signalized GCPs and 20 check points were distributed in the study area and measured with dualfrequency GPS via RTK technique with horizontal accuracy of σ = 1.5 cm and vertical accuracy of σ = 2.3 cm. results of direct georeferencing are compared to these points and experimental results show that decimeter accuracy level for 3D points cloud with proposed system is achievable, that is suitable

  18. SU-E-T-490: Independent Three-Dimensional (3D) Dose Verification of VMAT/SBRT Using EPID and Cloud Computing

    SciTech Connect

    Ding, A; Han, B; Bush, K; Wang, L; Xing, L

    2015-06-15

    Purpose: Dosimetric verification of VMAT/SBRT is currently performed on one or two planes in a phantom with either film or array detectors. A robust and easy-to-use 3D dosimetric tool has been sought since the advent of conformal radiation therapy. Here we present such a strategy for independent 3D VMAT/SBRT plan verification system by a combined use of EPID and cloud-based Monte Carlo (MC) dose calculation. Methods: The 3D dosimetric verification proceeds in two steps. First, the plan was delivered with a high resolution portable EPID mounted on the gantry, and the EPID-captured gantry-angle-resolved VMAT/SBRT field images were converted into fluence by using the EPID pixel response function derived from MC simulations. The fluence was resampled and used as the input for an in-house developed Amazon cloud-based MC software to reconstruct the 3D dose distribution. The accuracy of the developed 3D dosimetric tool was assessed using a Delta4 phantom with various field sizes (square, circular, rectangular, and irregular MLC fields) and different patient cases. The method was applied to validate VMAT/SBRT plans using WFF and FFF photon beams (Varian TrueBeam STX). Results: It was found that the proposed method yielded results consistent with the Delta4 measurements. For points on the two detector planes, a good agreement within 1.5% were found for all the testing fields. Patient VMAT/SBRT plan studies revealed similar level of accuracy: an average γ-index passing rate of 99.2± 0.6% (3mm/3%), 97.4± 2.4% (2mm/2%), and 72.6± 8.4 % ( 1mm/1%). Conclusion: A valuable 3D dosimetric verification strategy has been developed for VMAT/SBRT plan validation. The technique provides a viable solution for a number of intractable dosimetry problems, such as small fields and plans with high dose gradient.

  19. Applying 3D Full Waveform Inversion in resolving fracture damage zones around a modelled geological disposal facility in granite

    NASA Astrophysics Data System (ADS)

    Bentham, H. L. M.; Morgan, J. V.; Angus, D. A.

    2016-12-01

    The UK has a large volume of high level and intermediate level radioactive waste and government policy is to dispose of this waste in a Geological Disposal Facility (GDF). This will be a highly-engineered facility capable of isolating radioactive waste within multiple protective barriers, deep underground, to ensure that no harmful quantities of radioactivity ever reach the surface environment. Although no specific GDF site in the UK has been chosen, granite is one of the candidate host rocks due to its strength, in engineering terms, and because of its low permeability in consideration of groundwater movement. We design time-lapse seismic surveys to characterise geological models of naturally fractured granite with GDF-related tunnel damage zones at a potential disposal depth of 1000 m (the UK GDF might be shallower). Additionally, we use effective medium models to calculate the velocity change when the fracture density is increased in the damage zones, and find a reduction of 60 m/s in P-wave velocity when the fracture density is doubled. Next, we simulate seismic surveys and apply 3D Full Waveform Inversion (FWI) to see how well we can recover the low-velocity damage zones. Furthermore we evaluate the effectiveness of using a survey design consisting of surface and tunnel receivers (a combined array) to resolve the target. After applying FWI we find the velocity anomaly within the damage zone can be resolved to within 2 m/s (3%) and the shape of the damage zone is resolved to 12.5 m (within a single grid cell). Using the combined array we are able to resolve the anomaly strength and shape more completely. When we add further complexity to the model by including tunnel infrastructure, we conclude the combined array is essential in recovering the tunnel damage zone. Our findings show that it is beneficial to use 3D FWI and novel survey designs for characterising subtle variations as may be present in granite, information that could assist in the GDF site selection

  20. High Temporal and Spatial Resolution 3D Time-Resolved Contrast-Enhanced MR Angiography of the Hands and Feet

    PubMed Central

    Haider, Clifton R.; Riederer, Stephen J.; Borisch, Eric A.; Glockner, James F.; Grimm, Roger C.; Hulshizer, Thomas C.; Macedo, Thanila A.; Mostardi, Petrice M.; Rossman, Phillip J.; Vrtiska, Terri J.; Young, Phillip M.

    2010-01-01

    Methods are described for generating 3D time-resolved contrast-enhanced MR angiograms of the hands and feet. Given targeted spatial resolution and frame times, it is shown that acceleration of about one order of magnitude or more is necessary. This is obtained by a combination of 2D Sensitivity Encoding (SENSE) and homodyne (HD) acceleration methods. Image update times from 3.4 to 6.8 sec are provided in conjunction with view sharing. Modular receiver coil arrays are described which can be designed to the targeted vascular region. Images representative of the technique are generated in the vasculature of the hands and feet in volunteers and in patient studies. PMID:21698702

  1. 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.

  2. 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

  3. Hourly resolved cloud modification factors in the ultraviolet

    NASA Astrophysics Data System (ADS)

    Staiger, H.; den Outer, P. N.; Bais, A. F.; Feister, U.; Johnsen, B.; Vuilleumier, L.

    2008-01-01

    Cloud impacts on the transfer of Ultraviolet (UV) radiation through the atmosphere can be assessed using a cloud modification factor (CMF). The total global solar irradiation has proven to be a solid basis to derive CMF's for the UV radiation (UV_CMF). Total global irradiance is frequently measured and forecasted by numerical weather prediction systems. Its advantage compared to for instance cloud cover is that measured solar global irradiance contains already the effect of multiple reflection between cloud layers, reflection between the sides of the clouds, as well as the distinct difference whether the solar disc is obscured by clouds or not. In the UV range clouds decrease the irradiance to a lesser extent than in the visible and infrared spectral range; Rayleigh scattering in the atmosphere yields a larger fraction of scatter radiation compared to that of light and infrared, hence, obscuring the solar disc will not totally block out the irradiation. Thus the relationship between CMF's for solar radiation and for UV-radiation is not straight forwards, but will depend on e.g. the solar zenith angle (SZA) and wavelength band or action spectrum in the UV considered. Den Outer et al. (2005) provide a UV_CMF algorithm on a daily base accounting for these influences. It requires as input a daily CMF in total global radiation (SOL_CMF) and the SZA at noon. The calculation of SOL-CMF uses the clear sky algorithm of the European Solar Radiation Atlas to account for varying turbidity impacts. The algorithm's capability to derive hourly UV_CMF's based on the SZA at the corresponding hour and its worldwide applicability is validated using hourly resolved observational data retrieved from the databases of the COST-Action 726 on "Long term changes and climatology of UV radiation over Europe" and the USDA UV-B Monitoring and Research Program. The model performance for hourly resolution is shown to be comparable in absolute and relative deviations from a measured mean smoothed

  4. On the Estimation of Forest Resources Using 3D Remote Sensing Techniques and Point Cloud Data

    NASA Astrophysics Data System (ADS)

    Karjalainen, Mika; Karila, Kirsi; Liang, Xinlian; Yu, Xiaowei; Huang, Guoman; Lu, Lijun

    2016-08-01

    In recent years, 3D capable remote sensing techniques have shown great potential in forest biomass estimation because of their ability to measure the forest canopy structure, tree height and density. The objective of the Dragon3 forest resources research project (ID 10667) and the supporting ESA young scientist project (ESA contract NO. 4000109483/13/I-BG) was to study the use of satellite based 3D techniques in forest tree height estimation, and consequently in forest biomass and biomass change estimation, by combining satellite data with terrestrial measurements. Results from airborne 3D techniques were also used in the project. Even though, forest tree height can be estimated from 3D satellite SAR data to some extent, there is need for field reference plots. For this reason, we have also been developing automated field plot measurement techniques based on Terrestrial Laser Scanning data, which can be used to train and calibrate satellite based estimation models. In this paper, results of canopy height models created from TerraSAR-X stereo and TanDEM-X INSAR data are shown as well as preliminary results from TLS field plot measurement system. Also, results from the airborne CASMSAR system to measure forest canopy height from P- and X- band INSAR are presented.

  5. A closed-form expression of the positional uncertainty for 3D point clouds.

    PubMed

    Bae, Kwang-Ho; Belton, David; Lichti, Derek D

    2009-04-01

    We present a novel closed-form expression of positional uncertainty measured by a near-monostatic and time-of-flight laser range finder with consideration of its measurement uncertainties. An explicit form of the angular variance of the estimated surface normal vector is also derived. This expression is useful for the precise estimation of the surface normal vector and the outlier detection for finding correspondence in order to register multiple three-dimensional point clouds. Two practical algorithms using these expressions are presented: a method for finding optimal local neighbourhood size which minimizes the variance of the estimated normal vector and a resampling method of point clouds.

  6. Sparsity-based fast CGH generation using layer-based approach for 3D point cloud model

    NASA Astrophysics Data System (ADS)

    Kim, Hak Gu; Jeong, Hyunwook; Ro, Yong Man

    2017-03-01

    Computer generated hologram (CGH) is becoming increasingly important for a 3-D display in various applications including virtual reality. In the CGH, holographic fringe patterns are generated by numerically calculating them on computer simulation systems. However, a heavy computational cost is required to calculate the complex amplitude on CGH plane for all points of 3D objects. This paper proposes a new fast CGH generation based on the sparsity of CGH for 3D point cloud model. The aim of the proposed method is to significantly reduce computational complexity while maintaining the quality of the holographic fringe patterns. To that end, we present a new layer-based approach for calculating the complex amplitude distribution on the CGH plane by using sparse FFT (sFFT). We observe the CGH of a layer of 3D objects is sparse so that dominant CGH is rapidly generated from a small set of signals by sFFT. Experimental results have shown that the proposed method is one order of magnitude faster than recently reported fast CGH generation.

  7. LIVAS: a 3-D multi-wavelength aerosol/cloud climatology based on CALIPSO and EARLINET

    NASA Astrophysics Data System (ADS)

    Amiridis, V.; Marinou, E.; Tsekeri, A.; Wandinger, U.; Schwarz, A.; Giannakaki, E.; Mamouri, R.; Kokkalis, P.; Binietoglou, I.; Solomos, S.; Herekakis, T.; Kazadzis, S.; Gerasopoulos, E.; Balis, D.; Papayannis, A.; Kontoes, C.; Kourtidis, K.; Papagiannopoulos, N.; Mona, L.; Pappalardo, G.; Le Rille, O.; Ansmann, A.

    2015-01-01

    We present LIVAS, a 3-dimentional multi-wavelength global aerosol and cloud optical climatology, optimized to be used for future space-based lidar end-to-end simulations of realistic atmospheric scenarios as well as retrieval algorithm testing activities. LIVAS database provides averaged profiles of aerosol optical properties for the potential space-borne laser operating wavelengths of 355, 532, 1064, 1570 and 2050 nm and of cloud optical properties at the wavelength of 532 nm. The global climatology is based on CALIPSO observations at 532 and 1064 nm and on aerosol-type-dependent spectral conversion factors for backscatter and extinction, derived from EARLINET ground-based measurements for the UV and scattering calculations for the IR wavelengths, using a combination of input data from AERONET, suitable aerosol models and recent literature. The required spectral conversion factors are calculated for each of the CALIPSO aerosol types and are applied to CALIPSO extinction and backscatter data correspondingly to the aerosol type retrieved by the CALIPSO aerosol classification scheme. A cloud climatology based on CALIPSO measurements at 532 nm is also provided, neglecting wavelength conversion due to approximately neutral scattering behavior of clouds along the spectral range of LIVAS. Averages of particle linear depolarization ratio profiles at 532 nm are provided as well. Finally, vertical distributions for a set of selected scenes of specific atmospheric phenomena (e.g., dust outbreaks, volcanic eruptions, wild fires, polar stratospheric clouds) are analyzed and spectrally converted so as to be used as case studies for space-borne lidar performance assessments. The final global climatology includes 4-year (1 January 2008-31 December 2011) time-averaged CALIPSO data on a uniform grid of 1×1 degree with the original high vertical resolution of CALIPSO in order to ensure realistic simulations of the atmospheric variability in lidar end-to-end simulations.

  8. Status report on the 'Merging' of the Electron-Cloud Code POSINST with the 3-D Accelerator PIC CODE WARP

    SciTech Connect

    Vay, J.-L.; Furman, M.A.; Azevedo, A.W.; Cohen, R.H.; Friedman, A.; Grote, D.P.; Stoltz, P.H.

    2004-04-19

    We have integrated the electron-cloud code POSINST [1] with WARP [2]--a 3-D parallel Particle-In-Cell accelerator code developed for Heavy Ion Inertial Fusion--so that the two can interoperate. Both codes are run in the same process, communicate through a Python interpreter (already used in WARP), and share certain key arrays (so far, particle positions and velocities). Currently, POSINST provides primary and secondary sources of electrons, beam bunch kicks, a particle mover, and diagnostics. WARP provides the field solvers and diagnostics. Secondary emission routines are provided by the Tech-X package CMEE.

  9. A new approach for semi-automatic rock mass joints recognition from 3D point clouds

    NASA Astrophysics Data System (ADS)

    Riquelme, Adrián J.; Abellán, A.; Tomás, R.; Jaboyedoff, M.

    2014-07-01

    Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information - synthetic and 3D scanned data - were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

  10. Three-dimensional turbulence-resolving modeling of the Venusian cloud layer and induced gravity waves

    NASA Astrophysics Data System (ADS)

    Lefèvre, Maxence; Spiga, Aymeric; Lebonnois, Sébastien

    2017-01-01

    The impact of the cloud convective layer of the atmosphere of Venus on the global circulation remains unclear. The recent observations of gravity waves at the top of the cloud by the Venus Express mission provided some answers. These waves are not resolved at the scale of global circulation models (GCM); therefore, we developed an unprecedented 3-D turbulence-resolving large-eddy simulations (LES) Venusian model using the Weather Research and Forecast terrestrial model. The forcing consists of three different heating rates: two radiative ones for solar and infrared and one associated with the adiabatic cooling/warming of the global circulation. The rates are extracted from the Laboratoire de Météorlogie Dynamique Venus GCM using two different cloud models. Thus, we are able to characterize the convection and associated gravity waves in function of latitude and local time. To assess the impact of the global circulation on the convective layer, we used rates from a 1-D radiative-convective model. The resolved layer, taking place between 1.0 × 105 and 3.8 × 104 Pa (48-53 km), is organized as polygonal closed cells of about 10 km wide with vertical wind of several meters per second. The convection emits gravity waves both above and below the convective layer leading to temperature perturbations of several tenths of kelvin with vertical wavelength between 1 and 3 km and horizontal wavelength from 1 to 10 km. The thickness of the convective layer and the amplitudes of waves are consistent with observations, though slightly underestimated. The global dynamics heating greatly modify the convective layer.

  11. Three-dimensional turbulence-resolving modeling of the Venusian cloud layer and induced gravity waves

    NASA Astrophysics Data System (ADS)

    Lefèvre, Maxence; Spiga, Aymeric; Lebonnois, Sébastien

    2017-04-01

    The impact of the cloud convective layer of the atmosphere of Venus on the global circulation remains unclear. The recent observations of gravity waves at the top of the cloud by the Venus Express mission provided some answers. These waves are not resolved at the scale of global circulation models (GCM), therefore we developed an unprecedented 3D turbulence-resolving Large-Eddy Simulations (LES) Venusian model (Lefèvre et al, 2016 JGR Planets) using the Weather Research and Forecast terrestrial model. The forcing consists of three different heating rates : two radiative ones for solar and infrared and one associated with the adiabatic cooling/warming of the global circulation. The rates are extracted from the Laboratoire de Météorlogie Dynamique (LMD) Venus GCM using two different cloud models. Thus we are able to characterize the convection and associated gravity waves in function of latitude and local time. To assess the impact of the global circulation on the convective layer, we used rates from a 1D radiative-convective model. The resolved layer, taking place between 1.0 105 and 3.8 104 Pa (48-53 km), is organized as polygonal closed cells of about 10 km wide with vertical wind of several meters per second. The convection emits gravity waves both above and below the convective layer leading to temperature perturbations of several tenths of Kelvin with vertical wavelength between 1 and 3 km and horizontal wavelength from 1 to 10 km. The thickness of the convective layer and the amplitudes of waves are consistent with observations, though slightly underestimated. The global dynamics heating greatly modify the convective layer.

  12. 3D Moving-Mesh Simulations of Galactic Center Cloud G2

    NASA Astrophysics Data System (ADS)

    Wilson, Julia; Fragile, P. C.; Anninos, P.; Murray, S. D.

    2013-01-01

    Using three-dimensional, moving-mesh simulations, we investigate the future evolution of the recently discovered gas cloud G2 traveling through the galactic center. We consider the case of a spherical cloud initially in pressure equilibrium with the background. Our suite of simulations explores the following parameters: the equation of state, radial profiles of the background gas, and start times for the evolution. Our primary focus is on how the fate of this cloud will affect the future activity of Sgr A*. From our simulations we expect an average feeding rate in the range of 5 - 19 × 10-8M⊙ yr-1 beginning in 2013 and lasting for at least 7 years (our simulations stop in year 2020). The accretion varies by less than a factor of three on timescales ≤ 1 month, and shows no more than a factor of 10 difference between the maximum and minimum observed rates within any given model. These rates are comparable to the current estimated accretion rate in the immediate vicinity of Sgr A*, although they represent only a small (≤ 5%) increase over the current expected feeding rate at the effective inner boundary of our simulations (r = 750RS ≈ 1015 cm), where RS is the Schwarzschild radius of the black hole. Therefore, the break up of cloud G2 may have only a minimal effect on the brightness and variability of Sgr A* over the next decade. This is because current models of the galactic center predict that most of the gas will be caught up in outflows. However, if the accreted G2 material can remain cold, it may not mix well with the hot, diffuse background gas, and instead accrete efficiently onto Sgr A*. Further observations of G2 will give us an unprecedented opportunity to test this idea. The break up of the cloud itself may also be observable. By tracking the amount of cloud energy that is dissipated during our simulations, we are able to get a rough estimate of the luminosity associated with its tidal disruption; we find values of a few 1036 erg s-1.

  13. Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images

    NASA Astrophysics Data System (ADS)

    Vetrivel, Anand; Gerke, Markus; Kerle, Norman; Vosselman, George

    2015-07-01

    Point clouds generated from airborne oblique images have become a suitable source for detailed building damage assessment after a disaster event, since they provide the essential geometric and radiometric features of both roof and façades of the building. However, they often contain gaps that result either from physical damage or from a range of image artefacts or data acquisition conditions. A clear understanding of those reasons, and accurate classification of gap-type, are critical for 3D geometry-based damage assessment. In this study, a methodology was developed to delineate buildings from a point cloud and classify the present gaps. The building delineation process was carried out by identifying and merging the roof segments of single buildings from the pre-segmented 3D point cloud. This approach detected 96% of the buildings from a point cloud generated using airborne oblique images. The gap detection and classification methods were tested using two other data sets obtained with Unmanned Aerial Vehicle (UAV) images with a ground resolution of around 1-2 cm. The methods detected all significant gaps and correctly identified the gaps due to damage. The gaps due to damage were identified based on the surrounding damage pattern, applying Gabor wavelets and a histogram of gradient orientation features. Two learning algorithms - SVM and Random Forests were tested for mapping the damaged regions based on radiometric descriptors. The learning model based on Gabor features with Random Forests performed best, identifying 95% of the damaged regions. The generalization performance of the supervised model, however, was less successful: quality measures decreased by around 15-30%.

  14. Explicit Simulation of Aerosol Physics in a Cloud-Resolving Model: Aerosol Transport and Processing in the Free Troposphere.

    NASA Astrophysics Data System (ADS)

    Ekman, Annica M. L.; Wang, Chien; Ström, Johan; Krejci, Radovan

    2006-02-01

    Large concentrations of small aerosols have been previously observed in the vicinity of anvils of convective clouds. A 3D cloud-resolving model (CRM) including an explicit size-resolving aerosol module has been used to examine the origin of these aerosols. Five different types of aerosols are considered: nucleation mode sulfate aerosols (here defined by 0 d 5.84 nm), Aitken mode sulfate aerosols (here defined by 5.84 nm d 31.0 nm), accumulation mode sulfate aerosols (here defined by d 31.0 nm), mixed aerosols, and black carbon aerosols.The model results suggest that approximately 10% of the initial boundary layer number concentration of Aitken mode aerosols and black carbon aerosols are present at the top of the convective cloud as the cloud reaches its decaying state. The simulated average number concentration of Aitken mode aerosols in the cloud anvil (1.6 × 104 cm-3) is in the same order of magnitude as observations. Thus, the model results strongly suggest that vertical convective transport, particularly during the active period of the convection, is responsible for a major part of the appearance of high concentrations of small aerosols (corresponding to the Aitken mode in the model) observed in the vicinity of cloud anvils.There is some formation of new aerosols within the cloud, but the formation is small. Nucleation mode aerosols are also efficiently scavenged through impaction scavenging by precipitation. Accumulation mode and mixed mode aerosols are efficiently scavenged through nucleation scavenging and their concentrations in the cloud anvil are either very low (mixed mode) or practically zero (accumulation mode).In addition to the 3D CRM, a box model, including important features of the aerosol module of the 3D model, has been used to study the formation of new aerosols after the cloud has evaporated. The possibility of these aerosols to grow to suitable cloud condensation or ice nuclei size is also examined. Concentrations of nucleation mode aerosols

  15. Parallel simulations of aerosol influence on clouds using cloud-resolving and single-column models

    NASA Astrophysics Data System (ADS)

    Ovtchinnikov, Mikhail; Ghan, Steven J.

    2005-08-01

    The influence of the cloud condensation nucleus (CCN) concentration on the properties of low-level clouds under the conditions observed over the north central Oklahoma on 24-25 September 1997 is examined in a series of 18-hour simulations using a single-column model (SCM) and a cloud-resolving model (CM). Both models predict higher droplet concentration, smaller droplet size, and larger liquid water path in a "polluted" case (CCN concentration = 1000 cm-3) than in a clean case (CCN concentration = 250 cm-3), suggesting that the first and the second indirect effects act in unison under the considered conditions. A comparison of the simulations using the SCM and CM with the same two-moment bulk microphysics parameterization highlights the dominant effect of the dynamical framework on both microphysical and macrophysical properties of modeled cloud. This effect is much stronger than the variations in each of the models resulting from changing CCN concentrations. However, the relative liquid water path sensitivity to CCN concentration is similar between the SCM and CM simulations. The CM simulations with the size-resolved and the two-moment bulk microphysical parameterization yield nearly identical structure of boundary layer. Even though these simulations are in much closer agreement with each other than they are with the SCM results, the variance from the microphysics treatment is still comparable to the effect of quadrupling CCN concentration.

  16. The 3D Radiative Effects of Clouds in Aerosol Retrieval: Can we Remove Them?

    SciTech Connect

    Kassianov, Evgueni I.; Ovchinnikov, Mikhail; Berg, Larry K.; McFarlane, Sally A.; Flynn, Connor J.; Ferrare, Richard; Hostetler, Chris A.

    2009-09-30

    We outline a new method, called the ratio method, developed to retrieve aerosol optical depth (AOD) under broken cloud conditions and present validation results from sensitivity and case studies. Results of the sensitivity study demonstrate that the ratio method, which exploits ratios of reflectances in the visible spectral range, has the potential for accurate AOD retrievals under different observational conditions and random errors in input data. Also, we examine the performance of the ratio method using aircraft data collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS). Results of the case study suggest that the ratio method has the ability to retrieve AOD from multi-spectral aircraft observations of the reflected solar radiation.

  17. The role of boundary layer aerosol particles for the development of deep convective clouds: A high-resolution 3D model with detailed (bin) microphysics applied to CRYSTAL-FACE

    NASA Astrophysics Data System (ADS)

    Leroy, Delphine; Wobrock, Wolfram; Flossmann, Andrea I.

    2009-01-01

    This paper reproduces aircraft microphysical measurements using a three-dimensional model with bin resolved microphysics and is then used to analyze in particular the role of boundary layer aerosol particles in the anvil and the ice phase. The simulated case is a convective cloud which develops a large anvil of around 10 km height, which was sampled during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers — Florida Area Cirrus Experiment (CRYSTAL-FACE). The model couples the 3D dynamics of a cloud scale model with a detailed mixed phase microphysical code. The microphysical package considers the evolution of the wet aerosol particles, drop and ice crystal spectra on size grids with 39 bins. With this model hereafter called DESCAM 3D, we are able to simulate the cloud with features close to those observed and to provide explanations of the observed phenomena concerning cloud microphysics as well as cloud dynamics. The same CRYSTAL-FACE cloud has already been simulated by other groups using a similar model. They investigated the role of mid-tropospheric aerosol particles versus boundary layer aerosol on the microphysical properties of the anvil. Similar simulations with our DESCAM 3D lead to quite different results. Reducing the number of mid-tropospheric aerosol particles causes only minor changes in the cloud anvil. However, changing the aerosol particle spectrum in the boundary layer from clean to polluted conditions modifies strongly the dynamical evolution of the convective clouds and thus impacts significantly on the microphysical properties of the anvil. Possible reasons for the differences are discussed.

  18. Sensitivity studies of developing convection in a cloud-resolving model

    NASA Astrophysics Data System (ADS)

    Petch, J. C.

    2006-01-01

    Cloud-resolving models (CRMs) remain an important tool for providing detailed process information about convection. In this short paper I focus on the development of deep convection and consider what can be considered a minimum expense benchmark simulation for comparison with a numerical weather-prediction model. To decide this a range of sensitivity studies are presented to aspects of the experimental set-up which strongly impact the computational expense. Many of the sensitivities shown in these CRM experiments are quite different to those seen in previous papers which have tended to focus more on deep active convection. Here it is shown that for the case-study presented a minimum expense benchmark simulation must be a 3D simulation. A 200 m horizontal grid length and a domain of 25 km are also required to capture the most important processes.

  19. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

    PubMed Central

    Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

    2017-01-01

    The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

  20. A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds.

    PubMed

    Dorninger, Peter; Pfeifer, Norbert

    2008-11-17

    Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects.

  1. A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

    PubMed Central

    Dorninger, Peter; Pfeifer, Norbert

    2008-01-01

    Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects. PMID:27873931

  2. a Semi-Automated Point Cloud Processing Methodology for 3d Cultural Heritage Documentation

    NASA Astrophysics Data System (ADS)

    Kıvılcım, C. Ö.; Duran, Z.

    2016-06-01

    The preliminary phase in any architectural heritage project is to obtain metric measurements and documentation of the building and its individual elements. On the other hand, conventional measurement techniques require tremendous resources and lengthy project completion times for architectural surveys and 3D model production. Over the past two decades, the widespread use of laser scanning and digital photogrammetry have significantly altered the heritage documentation process. Furthermore, advances in these technologies have enabled robust data collection and reduced user workload for generating various levels of products, from single buildings to expansive cityscapes. More recently, the use of procedural modelling methods and BIM relevant applications for historic building documentation purposes has become an active area of research, however fully automated systems in cultural heritage documentation still remains open. In this paper, we present a semi-automated methodology, for 3D façade modelling of cultural heritage assets based on parametric and procedural modelling techniques and using airborne and terrestrial laser scanning data. We present the contribution of our methodology, which we implemented in an open source software environment using the example project of a 16th century early classical era Ottoman structure, Sinan the Architect's Şehzade Mosque in Istanbul, Turkey.

  3. Fusion Render Cloud System for 3D Contents Using a Super Computer

    NASA Astrophysics Data System (ADS)

    Choi, E.-Jung; Kim, Seoksoo

    This study develops a SOHO RenderFarm system suitable for a lab environment through data collection and professional education, implements a user environment which is the same as a super computer, analyzes rendering problems that may arise from use of a super computer and then designs a FRC(Fusion Render Cloud) system. Also, clients can access the SOHO RenderFarm system through networks, and the FRC system completed in a test environment can be interlinked with external networks of a super computer.

  4. A CANDELS-3D-HST synergy: Resolved star formation patterns at 0.7 < z < 1.5

    SciTech Connect

    Wuyts, Stijn; Förster Schreiber, Natascha M.; Genzel, Reinhard; Lutz, Dieter; Rosario, David; Nelson, Erica J.; Van Dokkum, Pieter G.; Momcheva, Ivelina; Brammer, Gabe; Chang, Yu-Yen; Faber, Sandra M.; Franx, Marijn; Fumagalli, Mattia; Kocevski, Dale D.; Lundgren, Britt; McGrath, Elizabeth J.; Skelton, Rosalind E.; and others

    2013-12-20

    We analyze the resolved stellar populations of 473 massive star-forming galaxies at 0.7 < z < 1.5, with multi-wavelength broadband imaging from CANDELS and Hα surface brightness profiles at the same kiloparsec resolution from 3D-HST. Together, this unique data set sheds light on how the assembled stellar mass is distributed within galaxies, and where new stars are being formed. We find the Hα morphologies to resemble more closely those observed in the ACS I band than in the WFC3 H band, especially for the larger systems. We next derive a novel prescription for Hα dust corrections, which accounts for extra extinction toward H II regions. The prescription leads to consistent star formation rate (SFR) estimates and reproduces the observed relation between the Hα/UV luminosity ratio and visual extinction, on both a pixel-by-pixel and a galaxy-integrated level. We find the surface density of star formation to correlate with the surface density of assembled stellar mass for spatially resolved regions within galaxies, akin to the so-called 'main sequence of star formation' established on a galaxy-integrated level. Deviations from this relation toward lower equivalent widths are found in the inner regions of galaxies. Clumps and spiral features, on the other hand, are associated with enhanced Hα equivalent widths, bluer colors, and higher specific SFRs compared to the underlying disk. Their Hα/UV luminosity ratio is lower than that of the underlying disk, suggesting that the ACS clump selection preferentially picks up those regions of elevated star formation activity that are the least obscured by dust. Our analysis emphasizes that monochromatic studies of galaxy structure can be severely limited by mass-to-light ratio variations due to dust and spatially inhomogeneous star formation histories.

  5. Size resolved simulation of a tropospheric multiphase cloud model

    NASA Astrophysics Data System (ADS)

    Majdik, Z.; Herrmann, H.

    2003-04-01

    The detailed and extended chemical mechanism CAPRAM 2.4 (MODAC mechanism, Chemical Aqueous Phase Radical Mechanism, Model Development for Tropospheric Aerosol and Cloud Chemistry, Herrmann et al., 2000, Ervens et al., 2002, http://www.tropos.de/CHEMIE/multimod/CAPRAM/CAPRAM24.pdf) coupled to the gas phase mechanism RACM (Regional Atmospheric Chemistry Mechanism, Stockwell et al., 1997) was applied to a size-segregated system in order to investigate the influence of size and liquid water distribution on the mass transport processes and on the multiphase chemistry in cloud droplets for three different CAPRAM standard scenarios. Uptake processes of soluble species are included in the mechanism following the approach by Schwartz (1986) considering gas phase diffusion, mass accommodation coefficients, Henry solubility and chemical reaction within the aqueous phase. The calculations were performed considering a different number of size bins (n=1,2,3,4,5,10,20,30,50) for the particle size range 1 µm < radius < 64 µm assuming an idealized lognormal distribution. Box model simulations showed that uptake processes are sensitive to the size distribution which affects the concentration levels both in the gas and particle phase. Interesting size effect can be observed in the iron redox system (marine scenario) during the night. Increasing the number of size bins causes higher Fe(III) concentration, [Fe(III)]. At the same time [Fe(II)] decreases. [Fe(III)] reaches values of about 1.5x10-8 cm-3 for the monodisperse and 3.5x10-8 cm-3 for the size resolved case. [Fe(II)] reaches a value of about 1.5x10-8 cm-3 in the size resolved system and a value of 3.5x10-8 cm-3 in the monodisperse system. The biggest change occurs in the case of the marine scenario due to the higher contribution of phase transfer processes compared to the urban and remote scenario.

  6. What can Cloud-Resolving Models Tell us About Critical Phenomena in Atmospheric Precipitation?

    NASA Astrophysics Data System (ADS)

    Krueger, S. K.; Kochanski, A.

    2009-12-01

    Recent work suggests that observations of Tropical precipitation conform to properties associated with critical phenomena of other systems (Peters and Neelin 2006). The precipitation retrievals are averages over 25-km by 25-km areas and are snapshots in time, and therefore unable to reveal the underlying, smaller-scale physical processes. We are using a 3D cloud-resolving model (CRM) to resolve these processes in space and time, and thereby allow us to investigate the underlying physics in detail. The CRM was run over a large domain (1000 km by 1000 km) for a long time (~10 days) in order to adequately sample the rare large events. In addition, we are using results from a 4-year global simulation using a climate model based on the multi-scale modeling framework (MMF). Whereas conventional parameterizations are based on statistical theories involving uncertain closure assumptions, MMFs represent cloud processes on their native scales by embedding a 2D CRM with a 4-km horizontal grid size in each climate model grid column. We have analyzed the model results following the methodology of Peters and Neelin. We used the results to produce rainfall rates conditioned on column water vapor and column temperature over the Tropical oceans. We have also analyzed additional statistical aspects of Tropical convection in the 3D CRM simulations that are related to critical behavior. We have found that: (1) CRMs are able to reproduce nearly all of the observed statistics of strong convective precipitation over tropical oceans. (2) CRMs and MMFs do not generally reproduce the observed roll-off of precipitation rate at large column water vapor values. (3) Analysis of CRM results suggests that many of the observed features are due to the tight coupling between dynamics and moist thermodynamics in convective updrafts.

  7. Structurally Resolved Abundances and Depletions in the Rho OPH Cloud

    NASA Astrophysics Data System (ADS)

    Seab, C.

    1995-07-01

    The mechanism that determines the pattern of depletion ofelements in the interstellar medium has been a problem for along time. It is clear that some of the most refractoryelements such as Si, Fe, and Mg, are heavily depleted onto theinterstellar grains. On the other hand, some elements such asS and Zn are normally either undepleted or very lightlydepleted. The difference between the two cases is notunderstood. We propose to address this question with adetailed study of the depletion patterns in the Rho Ophiuchicloud. This study is strongly based on a combination of thecapabilities of two modern instruments: the GHRS for high-resolution UV data, and the Ultra High Resolution Facility(UHRF) of the AAT. This instrument has been used to obtain NaI line profiles in the Rho Oph cloud with a resolution ofR=1,000,000. The combination of these two types of data willbe used to resolve the velocity structure of the elementdepletions in the cloud.

  8. Historical Buildings Models and Their Handling via 3d Survey: from Points Clouds to User-Oriented Hbim

    NASA Astrophysics Data System (ADS)

    Chiabrando, F.; Sammartano, G.; Spanò, A.

    2016-06-01

    This paper retraces some research activities and application of 3D survey techniques and Building Information Modelling (BIM) in the environment of Cultural Heritage. It describes the diffusion of as-built BIM approach in the last years in Heritage Assets management, the so-called Built Heritage Information Modelling/Management (BHIMM or HBIM), that is nowadays an important and sustainable perspective in documentation and administration of historic buildings and structures. The work focuses the documentation derived from 3D survey techniques that can be understood like a significant and unavoidable knowledge base for the BIM conception and modelling, in the perspective of a coherent and complete management and valorisation of CH. It deepens potentialities, offered by 3D integrated survey techniques, to acquire productively and quite easilymany 3D information, not only geometrical but also radiometric attributes, helping the recognition, interpretation and characterization of state of conservation and degradation of architectural elements. From these data, they provide more and more high descriptive models corresponding to the geometrical complexity of buildings or aggregates in the well-known 5D (3D + time and cost dimensions). Points clouds derived from 3D survey acquisition (aerial and terrestrial photogrammetry, LiDAR and their integration) are reality-based models that can be use in a semi-automatic way to manage, interpret, and moderately simplify geometrical shapes of historical buildings that are examples, as is well known, of non-regular and complex geometry, instead of modern constructions with simple and regular ones. In the paper, some of these issues are addressed and analyzed through some experiences regarding the creation and the managing of HBIMprojects on historical heritage at different scales, using different platforms and various workflow. The paper focuses on LiDAR data handling with the aim to manage and extract geometrical information; on

  9. Cloud and Circulation Feedbacks in a Near-Global Aquaplanet Cloud-Resolving Model

    NASA Astrophysics Data System (ADS)

    Narenpitak, P.; Bretherton, C. S.; Khairoutdinov, M.

    2016-12-01

    A near-global aquaplanet cloud-resolving model (CRM) is used to investigate cloud feedbacks due to three climate perturbations: a uniform 4 K increase in sea-surface temperature (SST), a quadrupling of CO2 concentration, and both combined. The CRM has a horizontal resolution of 4 km with no cumulus parameterization. It is a zonally periodic 20480 km-long tropical channel, spanning 46°S-N with rigid walls. An equatorially symmetric QOBS SST distribution is specified for the control simulation. After spin-up, 80 days are analyzed for the control and 4 K SST increase simulations, and 40 days for the simulations with quadrupled CO2. The 4 K SST increase induces a statistically significant increase in subtropical low cloud but decreases midlatitude cloud; its domain-mean shortwave cloud feedbacks are slightly positive. CO2 quadrupling causes a slight shallowing and a statistically insignificant reduction of subtropical low cloud. These results are qualitatively consistent with aquaplanet versions of some conventionally-parameterized climate models [Medeiros et al., 2015, Clim Dyn], and with a superparameterized real-geography version of the Community Atmosphere Model, Version 4 [Bretherton et al., 2014, JAMES], which uses CRMs similar to this study. The geographic structure of warming-induced low cloud changes is strongly correlated with the associated changes in estimated inversion strength (EIS). The EIS increases by 1 K in the subtropics but decreases in the midlatitudes due to poleward jet shifts. Clear-sky boundary-layer radiative cooling plays a key role in the subtropical low cloud increase, as it further destabilizes the cloud layer and produces a positive feedback, in agreement with a hypothesis from Wyant et al. [2009, JAMES]. The subtropical low cloud increase is also associated with stronger vertical velocity variance, although there is little change in the vertical profile of buoyancy flux. The zonal variance of column relative humidity is compared between

  10. Cloud GIS and 3d Modelling to Enhance Sardinian Late Gothic Architectural Heritage

    NASA Astrophysics Data System (ADS)

    Pisu, C.; Casu, P.

    2013-07-01

    This work proposes the documentation, virtual reconstruction and spreading of architectural heritage through the use of software packages that operate in cloud computing. Cloud computing makes available a variety of applications and tools which can be effective both for the preparation and for the publication of different kinds of data. We tested the versatil ity and ease of use of such documentation tools in order to study a particular architectural phenomenon. The ultimate aim is to develop a multi-scale and multi-layer information system, oriented to the divulgation of Sardinian late gothic architecture. We tested the applications on portals of late Gothic architecture in Sardinia. The actions of conservation, protection and enhancement of cultural heritage are all founded on the social function that can be reached only through the widest possible fruition by the community. The applications of digital technologies on cultural heritage can contribute to the construction of effective communication models that, relying on sensory and emotional involvement of the viewer, can attract a wider audience to cultural content.

  11. Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data

    NASA Astrophysics Data System (ADS)

    Dittrich, André; Weinmann, Martin; Hinz, Stefan

    2017-04-01

    In photogrammetry, remote sensing, computer vision and robotics, a topic of major interest is represented by the automatic analysis of 3D point cloud data. This task often relies on the use of geometric features amongst which particularly the ones derived from the eigenvalues of the 3D structure tensor (e.g. the three dimensionality features of linearity, planarity and sphericity) have proven to be descriptive and are therefore commonly involved for classification tasks. Although these geometric features are meanwhile considered as standard, very little attention has been paid to their accuracy and robustness. In this paper, we hence focus on the influence of discretization and noise on the most commonly used geometric features. More specifically, we investigate the accuracy and robustness of the eigenvalues of the 3D structure tensor and also of the features derived from these eigenvalues. Thereby, we provide both analytical and numerical considerations which clearly reveal that certain features are more susceptible to discretization and noise whereas others are more robust.

  12. The 3-D Tropical Convective Cloud Spectrum in AMIE Radar Observations and Global Climate Simulations

    SciTech Connect

    Schumacher, Courtney

    2015-08-31

    During the three years of this grant performance, the PI and her research group have made a number of significant contributions towards determining properties of tropical deep convective clouds and how models depict and respond to the heating associated with tropical convective systems. The PI has also been an active ARM/ASR science team member, including playing a significant role in AMIE and GoAmazon2014/5. She served on the DOE ASR radar science steering committee and was a joint chair of the Mesoscale Convective Organization group under the Cloud Life Cycle working group. This grant has funded a number of graduate students, many of them women, and the PI and her group have presented their DOE-supported work at various universities and national meetings. The PI and her group participated in the AMIE (2011-12) and GoAmazon2014/5 (2014-15) DOE field deployments that occurred in the tropical Indian Ocean and Brazilian Amazon, respectively. AMIE observational results (DePasquale et al. 2014, Feng et al. 2014, Ahmed and Schumacher 2015) focus on the variation and possible importance of Kelvin waves in various phases of the Madden-Julian Oscillation (MJO), on the synergy of the different wavelength radars deployed on Addu Atoll, and on the importance of humidity thresholds in the tropics on stratiform rain production. Much of the PIs GoAmazon2014/5 results to date relate to overviews of the observations made during the field campaign (Martin et al. 2015, 2016; Fuentes et al. 2016), but also include the introduction of the descending arm and its link to ozone transport from the mid-troposphere to the surface (Gerken et al. 2016). Vertical motion and mass flux profiles from GoAmazon (Giangrande et al. 2016) also show interesting patterns between seasons and provide targets for model simulations. Results from TWP-ICE (Schumacher et al. 2015), which took place in Darwin, Australia in 2006 show that vertical velocity retrievals from the profilers provide structure to

  13. Direct local building inundation depth determination in 3-D point clouds generated from user-generated flood images

    NASA Astrophysics Data System (ADS)

    Griesbaum, Luisa; Marx, Sabrina; Höfle, Bernhard

    2017-07-01

    In recent years, the number of people affected by flooding caused by extreme weather events has increased considerably. In order to provide support in disaster recovery or to develop mitigation plans, accurate flood information is necessary. Particularly pluvial urban floods, characterized by high temporal and spatial variations, are not well documented. This study proposes a new, low-cost approach to determining local flood elevation and inundation depth of buildings based on user-generated flood images. It first applies close-range digital photogrammetry to generate a geo-referenced 3-D point cloud. Second, based on estimated camera orientation parameters, the flood level captured in a single flood image is mapped to the previously derived point cloud. The local flood elevation and the building inundation depth can then be derived automatically from the point cloud. The proposed method is carried out once for each of 66 different flood images showing the same building façade. An overall accuracy of 0.05 m with an uncertainty of ±0.13 m for the derived flood elevation within the area of interest as well as an accuracy of 0.13 m ± 0.10 m for the determined building inundation depth is achieved. Our results demonstrate that the proposed method can provide reliable flood information on a local scale using user-generated flood images as input. The approach can thus allow inundation depth maps to be derived even in complex urban environments with relatively high accuracies.

  14. Analysis and numerical simulation of a real cell merger using a three-dimensional cloud resolving model

    NASA Astrophysics Data System (ADS)

    Karacostas, T.; Spiridonov, V.; Bampzelis, D.; Pytharoulis, I.; Tegoulias, I.; Tymbanidis, K.

    2016-03-01

    A three-dimensional cloud resolving model is used to study a real cell merger case that occurred on 10 August, 2008 over north-central Greece, causing heavy rainfall, hailfall and high-frequency lightning. Firstly, the storm is observed, analyzed and recorded using a C-band weather radar. Secondly, three distinct simulations are performed using a cloud resolving model. An unseeded simulation, in order to test the ability of the model to reproduce the structural and evolutionary properties of the storm and two seeded simulations in which seeding occurred before and after cell merging. Reflectivity fields are analyzed, horizontally and vertically, at different simulation times. The 3-D numerical simulations suggest that the merger process occurred by two or three isolated single-cells and formed during their SW-NE motion. The merging process apparently alters dynamical and microphysical properties through low and middle level forcing; increases cloud diameters and cloud depths, producing more graupel and ice particles and increases radar reflectivity values. Processed radar images depict a similar view of the storm structure, evolution and interactions of such merging processes. The model calculated maximum radar reflectivity values coincide with the recorded ones. Results indicate that seeding the cloud before its merging produces more positive effects on hail suppression than seeding after merging. These findings are quite important, in order to document the value of the cloud resolving model and its capability to simulate and reproduce the realistic storm processes and to provide a better understanding of the cloud dynamical and microphysical features related to different seeding approaches.

  15. Quantifying 3D ice cliff evolution with multi-temporal point clouds on the debris-covered Khumbu Glacier, Nepal

    NASA Astrophysics Data System (ADS)

    Watson, C. Scott; Quincey, Duncan; Smith, Mark; Carrivick, Jonathan; Rowan, Ann

    2017-04-01

    Observations of ice cliff retreat on debris-covered glaciers have until recently focused on point ablation stake measurements, which may not be representative of the melt rates across a heterogeneous cliff face. Here we present the first fully 3D assessment of spatio-temporal ice cliff evolution on Khumbu Glacier in the Everest region of Nepal. During three field campaigns (Nov 2015, May 2016, Oct 2016), nine ice cliffs were surveyed to enable 3D point cloud generation following a Structure-from-Motion with Multi-View Stereo (SfM-MVS) workflow. Multi-temporal point clouds were differenced using the M3C2 algorithm in Cloud Compare to calculate statistically significant 3D topographic change. Four out of nine cliffs persisted over the study, whereas five became buried under a layer of debris. The spatio-temporal evolution of ice cliffs was found to be dependent upon cliff-scale characteristics (e.g. height and aspect) and their topographic context (e.g. presence of a supraglacial pond and the back slope of the cliff). Thermal undercutting by a supraglacial pond maintained the cliff angle during retreat, which delayed burial by debris. The back slope of an ice cliff also determined its potential longevity, with a low back slope promoting continued retreat and a high back slope promoting burial under debris. Retreat rates Oct-2015 to May-2016 ranged from 0.46 - 1.50 cm d-1 (mean of 0.8 cm d-1) compared to 0.74 - 5.18 cm d-1 (mean of 2.5 cm d-1) during May-2016 to Oct-2016. Within a year, cliff retreat exceeded 8 m in several instances. Additionally, new cliffs formed and supraglacial ponds both expanded and drained. Quantifying these glacier surface dynamics therefore requires annual to sub-annual resolution assessments. These data will be used towards the parameterisation of ice cliff retreat into dynamic glacier models, which is essential to forecast the rates of glacier mass loss and subsequent effect on river discharge.

  16. Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud

    PubMed Central

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H.; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-01-01

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC). PMID:25076221

  17. Incremental Refinement of FAÇADE Models with Attribute Grammar from 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Dehbi, Y.; Staat, C.; Mandtler, L.; Pl¨umer, L.

    2016-06-01

    Data acquisition using unmanned aerial vehicles (UAVs) has gotten more and more attention over the last years. Especially in the field of building reconstruction the incremental interpretation of such data is a demanding task. In this context formal grammars play an important role for the top-down identification and reconstruction of building objects. Up to now, the available approaches expect offline data in order to parse an a-priori known grammar. For mapping on demand an on the fly reconstruction based on UAV data is required. An incremental interpretation of the data stream is inevitable. This paper presents an incremental parser of grammar rules for an automatic 3D building reconstruction. The parser enables a model refinement based on new observations with respect to a weighted attribute context-free grammar (WACFG). The falsification or rejection of hypotheses is supported as well. The parser can deal with and adapt available parse trees acquired from previous interpretations or predictions. Parse trees derived so far are updated in an iterative way using transformation rules. A diagnostic step searches for mismatches between current and new nodes. Prior knowledge on façades is incorporated. It is given by probability densities as well as architectural patterns. Since we cannot always assume normal distributions, the derivation of location and shape parameters of building objects is based on a kernel density estimation (KDE). While the level of detail is continuously improved, the geometrical, semantic and topological consistency is ensured.

  18. Calibration of an outdoor distributed camera network with a 3D point cloud.

    PubMed

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-07-29

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).

  19. The ICON model hierarchy: towards cloud resolving scales

    NASA Astrophysics Data System (ADS)

    Klocke, Daniel; Brueck, Matthias; Hohenegger, Cathy

    2017-04-01

    Convection permitting simulations for the tropical Atlantic region (9000x3300 km) are performed using the icosahedral non-hydrostatic (ICON) general circulation model, jointly developed by MPI-M and DWD. The motivation is: a.) better physical process understanding of cloud, convection and circulation (via connecting the small and large scales), b.) support of observational campaigns (mission and flight planning via providing a virtual test-best), in turn c.) use the corresponding observational data for modal evaluation and d.) thereby integrating research communities from measurements and modeling. Short forecast simulations of 36 hours are performed for over 60 days accompanying the NARVAL observations campaign in Dec 2013 and Aug 2016 using a grid spacing of 2.5 km and a 1.2 km in a nested domain. This data further serves to drive a second set of simulations in context to the HD(CP)2 project using 600, 300 and 150 m grid spacing. The model setups are related NWP setup of ICON, but the kilometer scale simulations explicitly treat convection and the sub-kilometer simulations are further using the 3D Smagorinsky turbulence parameterization (ICON-Large Eddy Model). As deep convection is a key process in tropical and subtropical regions, the explicit evolution of convection across a wide range of horizontal scales produces rich interactions with their environment and neighboring convective cells, producing emergent phenomena like cold pools, gravity waves, convective self-aggregation and even hurricanes.

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  2. Registration of 3D point clouds and meshes: a survey from rigid to nonrigid.

    PubMed

    Tam, Gary K L; Cheng, Zhi-Quan; Lai, Yu-Kun; Langbein, Frank C; Liu, Yonghuai; Marshall, David; Martin, Ralph R; Sun, Xian-Fang; Rosin, Paul L

    2013-07-01

    Three-dimensional surface registration transforms multiple three-dimensional data sets into the same coordinate system so as to align overlapping components of these sets. Recent surveys have covered different aspects of either rigid or nonrigid registration, but seldom discuss them as a whole. Our study serves two purposes: 1) To give a comprehensive survey of both types of registration, focusing on three-dimensional point clouds and meshes and 2) to provide a better understanding of registration from the perspective of data fitting. Registration is closely related to data fitting in which it comprises three core interwoven components: model selection, correspondences and constraints, and optimization. Study of these components 1) provides a basis for comparison of the novelties of different techniques, 2) reveals the similarity of rigid and nonrigid registration in terms of problem representations, and 3) shows how overfitting arises in nonrigid registration and the reasons for increasing interest in intrinsic techniques. We further summarize some practical issues of registration which include initializations and evaluations, and discuss some of our own observations, insights and foreseeable research trends.

  3. 3d Mixing In Hot-jupiter Atmospheres: Application To Tio Clouds On Hd209458b

    NASA Astrophysics Data System (ADS)

    Parmentier, Vivien; Showman, A. P.; Lian, Y.

    2012-10-01

    Like brown dwarfs, hot Jupiters exhibit atmospheric temperatures ranging from hundreds to thousands of Kelvins. But unlike them, they are highly 3D objects with strongly asymmetric heating and a huge day/night temperature contrast. Thus, many chemical species that can exist in gas phase on the dayside can condense and gravitationally settle on the nightside. The abundance of such species in the atmosphere therefore depends whether or not the atmospheric circulation can loft them vertically despite their tendency to gravitationally settle on the nightside. To understand the three-dimensional distribution of such species, we present global circulation models of HD209458b including passive tracers that advect with the three-dimensional flow, including a source/sink on the nightside to represent condensation and gravitational settling. We show that global advection patterns produce very strong vertical mixing that can keep particles lofted as long as the particles sizes are a few microns or less. A key point is that the region being vigorously mixed is stably stratified; the vertical mixing results not from small-scale convection but from the large-scale circulation driven by the day-night heating contrast. Although this vertical mixing is not diffusive in any rigorous sense, a comparison of our results with idealized diffusion models allows a rough estimate of the effective vertical eddy diffusivities in these atmospheres; we will present these diffusivities, which can be used in 1D models of the atmosphere. Moreover, we show that the models produce strong spatial and temporal variability in the tracer concentration that could result in observable variations in the secondary eclipse depth of hot Jupiters. Finally, we focus on TiO in HD209458b and show that the day-night cold trap would deplete TiO if it condenses into particles bigger than a few microns on the planet's night side, making it unable to create the observed stratosphere of the planet.

  4. Accelerated 3D echo-planar imaging with compressed sensing for time-resolved hyperpolarized (13) C studies.

    PubMed

    Geraghty, Benjamin J; Lau, Justin Y C; Chen, Albert P; Cunningham, Charles H

    2017-02-01

    To enable large field-of-view, time-resolved volumetric coverage in hyperpolarized (13) C metabolic imaging by implementing a novel data acquisition and image reconstruction method based on the compressed sensing framework. A spectral-spatial pulse for single-resonance excitation followed by a symmetric echo-planar imaging (EPI) readout was implemented for encoding a 72 × 18 cm(2) field of view at 5 × 5 mm(2) resolution. Random undersampling was achieved with blipped z-gradients during the ramp portion of the echo-planar imaging readout. The sequence and reconstruction were tested with phantom studies and consecutive in vivo hyperpolarized (13) C scans in rats. Retrospectively and prospectively undersampled data were compared on the basis of structural similarity in the reconstructed images and the quantification of the lactate-to-pyruvate ratio in rat kidneys. No artifacts or loss of resolution are evident in the compressed sensing reconstructed images acquired with the proposed sequence. Structural similarity analysis indicate that compressed sensing reconstructions can accurately recover spatial features in the metabolic images evaluated. A novel z-blip acquisition sequence for compressed sensing accelerated hyperpolarized (13) C 3D echo-planar imaging was developed and demonstrated. The close agreement in lactate-to-pyruvate ratios from both retrospectively and prospectively undersampled data from rats shows that metabolic information is preserved with acceleration factors up to 3-fold with the developed method. Magn Reson Med 77:538-546, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  5. Simulation of Subgrid Orographic Convection and Precipitation with 2-D Cloud-Resolving Models Embedded in a GCM Grid

    NASA Astrophysics Data System (ADS)

    Jung, J.; Arakawa, A.

    2015-12-01

    Through explicitly resolved cloud-scale processes by embedded 2-D cloud-resolving models (CRMs), the Multiscale Modeling Framework (MMF) known as the superparameterization has been reasonably successful to simulate various atmospheric events over a wide range of time scales. One thing to be justified is, however, if the influence of complex 3-D topography can be adequately represented by the embedded 2-D CRMs. In this study, simulations are performed in the presence of a variety of topography with embedded 3-D and 2-D CRMs in a single-column inactive GCM. Through the comparison between these simulations, it is demonstrated that the 2-D representation of topography is able to simulate the statistics of precipitation due to 3-D topography reasonably well as long as the topographic characteristics, such as the mean and standard deviation, are closely recognized. It is also shown that the use of two perpendicular sets of 2-D representations tends to reduce the error due to a 2-D representation.

  6. A Scalable Cloud Library Empowering Big Data Management, Diagnosis, and Visualization of Cloud-Resolving Models

    NASA Astrophysics Data System (ADS)

    Zhou, S.; Tao, W. K.; Li, X.; Matsui, T.; Sun, X. H.; Yang, X.

    2015-12-01

    A cloud-resolving model (CRM) is an atmospheric numerical model that can numerically resolve clouds and cloud systems at 0.25~5km horizontal grid spacings. The main advantage of the CRM is that it can allow explicit interactive processes between microphysics, radiation, turbulence, surface, and aerosols without subgrid cloud fraction, overlapping and convective parameterization. Because of their fine resolution and complex physical processes, it is challenging for the CRM community to i) visualize/inter-compare CRM simulations, ii) diagnose key processes for cloud-precipitation formation and intensity, and iii) evaluate against NASA's field campaign data and L1/L2 satellite data products due to large data volume (~10TB) and complexity of CRM's physical processes. We have been building the Super Cloud Library (SCL) upon a Hadoop framework, capable of CRM database management, distribution, visualization, subsetting, and evaluation in a scalable way. The current SCL capability includes (1) A SCL data model enables various CRM simulation outputs in NetCDF, including the NASA-Unified Weather Research and Forecasting (NU-WRF) and Goddard Cumulus Ensemble (GCE) model, to be accessed and processed by Hadoop, (2) A parallel NetCDF-to-CSV converter supports NU-WRF and GCE model outputs, (3) A technique visualizes Hadoop-resident data with IDL, (4) A technique subsets Hadoop-resident data, compliant to the SCL data model, with HIVE or Impala via HUE's Web interface, (5) A prototype enables a Hadoop MapReduce application to dynamically access and process data residing in a parallel file system, PVFS2 or CephFS, where high performance computing (HPC) simulation outputs such as NU-WRF's and GCE's are located. We are testing Apache Spark to speed up SCL data processing and analysis.With the SCL capabilities, SCL users can conduct large-domain on-demand tasks without downloading voluminous CRM datasets and various observations from NASA Field Campaigns and Satellite data to a

  7. Prospects of 3D mapping of the Galactic Centre clouds with X-ray polarimetry

    NASA Astrophysics Data System (ADS)

    Marin, F.; Karas, V.; Kunneriath, D.; Muleri, F.

    2014-07-01

    Despite past panchromatic observations of the innermost part of the Milky Way, the overall structure of the Galactic Centre (GC) remains enigmatic in terms of geometry. In this paper, we aim to show how polarimetry can probe the three-dimensional position of the molecular material in the central ˜100 pc of the GC. We investigate a model where the central supermassive black hole Sgr A* is radiatively coupled to a fragmented circumnuclear disc (CND), an elliptical twisted ring representative of the central molecular zone (CMZ), and the two main, bright molecular clouds Sgr B2 and Sgr C. 8-35 keV integrated polarization mapping reveals that Sgr B2 and Sgr C, situated at the two sides of the CMZ, present the highest polarization degrees (66.5 and 47.8 per cent, respectively), both associated with a polarization position angle ψ = 90° (normal to the scattering plane). The CND shows a lower polarization degree, 1.0 per cent with ψ = -20.5°, tracing the inclination of the CND with respect to the Galactic plane. The CMZ polarization is spatially variable. We also consider a range of spatial locations for Sgr A* and the reprocessing media, and investigate how the modelled three-dimensional geometry influences the resulting GC polarization. The two reflection nebulae are found to always produce high polarization degrees (≫10 per cent). We show that a 500 ks observation with a broad-band polarimeter could constrain the location and the morphology of the scattering material with respect to the emitting source, revealing the past activity of Sgr A*.

  8. Combination of Tls Point Clouds and 3d Data from Kinect v2 Sensor to Complete Indoor Models

    NASA Astrophysics Data System (ADS)

    Lachat, E.; Landes, T.; Grussenmeyer, P.

    2016-06-01

    The combination of data coming from multiple sensors is more and more applied for remote sensing issues (multi-sensor imagery) but also in cultural heritage or robotics, since it often results in increased robustness and accuracy of the final data. In this paper, the reconstruction of building elements such as window frames or door jambs scanned thanks to a low cost 3D sensor (Kinect v2) is presented. Their combination within a global point cloud of an indoor scene acquired with a terrestrial laser scanner (TLS) is considered. If the added elements acquired with the Kinect sensor enable to reach a better level of detail of the final model, an adapted acquisition protocol may also provide several benefits as for example time gain. The paper aims at analyzing whether the two measurement techniques can be complementary in this context. The limitations encountered during the acquisition and reconstruction steps are also investigated.

  9. 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

  10. Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

    NASA Technical Reports Server (NTRS)

    Putman, William M.

    2010-01-01

    NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

  11. Examining In-Cloud Convective Turbulence in Relation to Total Lightning and the 3D Wind Field of Severe Thunderstorms

    NASA Astrophysics Data System (ADS)

    Al-Momar, S. A.; Deierling, W.; Williams, J. K.; Hoffman, E. G.

    2014-12-01

    Convectively induced turbulence (CIT) is commonly listed as a cause or factor in weather-related commercial aviation accidents. In-cloud CIT is generated in part by shears between convective updrafts and downdrafts. Total lightning is also dependent on a robust updraft and the resulting storm electrification. The relationship between total lightning and turbulence could prove useful in operational aviation settings with the use of future measurements from the geostationary lightning mapper (GLM) onboard the GOES-R satellite. Providing nearly hemispheric coverage of total lightning, the GLM could help identify CIT in otherwise data-sparse locations. For a severe thunderstorm case on 7 June 2012 in northeast Colorado, in-cloud eddy dissipation rate estimates from the NCAR/NEXRAD Turbulence Detection Algorithm were compared with cloud electrification data from the Colorado Lightning Mapping Array and radar products from the Denver, Colorado WSR-88D. These comparisons showed that high concentrations of very high frequency (VHF) source densities emitted by lightning occurred near and downstream of the storm's convective core. Severe turbulence was also shown to occur near this area, extending near the melting level of the storm and spreading upward and outward. Additionally, increases/decreases in VHF sources and turbulence volumes occurred within a few minutes of each other; although, light turbulence was shown to increase near one storm's dissipation. This may be due to increased shear from the now downdraft dominate storm. The 3D wind field from this case, obtained by either a dual-Doppler or a Variational Doppler Radar Assimilation System (VDRAS) analysis, will also be examined to further study the relationships between total lightning and thunderstorm kinematics. If these results prove to be robust, lightning may serve as a strong indicator of the location of moderate or greater turbulence.

  12. Macro-to-micro interfacing to microfluidic channels using 3D-printed templates: application to time-resolved secretion sampling of endocrine tissue.

    PubMed

    Brooks, Jessica C; Ford, Katarena I; Holder, Dylan H; Holtan, Mark D; Easley, Christopher J

    2016-10-21

    Employing 3D-printed templates for macro-to-micro interfacing, a passively operated polydimethysiloxane (PDMS) microfluidic device was designed for time-resolved secretion sampling from primary murine islets and epidiymal white adipose tissue explants. Interfacing in similar devices is typically accomplished through manually punched or drilled fluidic reservoirs. We previously introduced the concept of using hand fabricated polymer inserts to template cell culture and sampling reservoirs into PDMS devices, allowing rapid stimulation and sampling of endocrine tissue. However, fabrication of the fluidic reservoirs was time consuming, tedious, and was prone to errors during device curing. Here, we have implemented computer-aided design and 3D printing to circumvent these fabrication obstacles. In addition to rapid prototyping and design iteration advantages, the ability to match these 3D-printed interface templates with channel patterns is highly beneficial. By digitizing the template fabrication process, more robust components can be produced with reduced fabrication variability. Herein, 3D-printed templates were used for sculpting millimetre-scale reservoirs into the above-channel, bulk PDMS in passively-operated, eight-channel devices designed for time-resolved secretion sampling of murine tissue. Devices were proven functional by temporally assaying glucose-stimulated insulin secretion from <10 pancreatic islets and glycerol secretion from 2 mm adipose tissue explants, suggesting that 3D-printed interface templates could be applicable to a variety of cells and tissue types. More generally, this work validates desktop 3D printers as versatile interfacing tools in microfluidic laboratories.

  13. Forecasting Lightning Threat using Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    McCaul, Eugene W., Jr.; Goodman, Steven J.; LaCasse, Katherine M.; Cecil, Daniel J.

    2008-01-01

    Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single

  14. See-Through Imaging of Laser-Scanned 3d Cultural Heritage Objects Based on Stochastic Rendering of Large-Scale Point Clouds

    NASA Astrophysics Data System (ADS)

    Tanaka, S.; Hasegawa, K.; Okamoto, N.; Umegaki, R.; Wang, S.; Uemura, M.; Okamoto, A.; Koyamada, K.

    2016-06-01

    We propose a method for the precise 3D see-through imaging, or transparent visualization, of the large-scale and complex point clouds acquired via the laser scanning of 3D cultural heritage objects. Our method is based on a stochastic algorithm and directly uses the 3D points, which are acquired using a laser scanner, as the rendering primitives. This method achieves the correct depth feel without requiring depth sorting of the rendering primitives along the line of sight. Eliminating this need allows us to avoid long computation times when creating natural and precise 3D see-through views of laser-scanned cultural heritage objects. The opacity of each laser-scanned object is also flexibly controllable. For a laser-scanned point cloud consisting of more than 107 or 108 3D points, the pre-processing requires only a few minutes, and the rendering can be executed at interactive frame rates. Our method enables the creation of cumulative 3D see-through images of time-series laser-scanned data. It also offers the possibility of fused visualization for observing a laser-scanned object behind a transparent high-quality photographic image placed in the 3D scene. We demonstrate the effectiveness of our method by applying it to festival floats of high cultural value. These festival floats have complex outer and inner 3D structures and are suitable for see-through imaging.

  15. Improving the representation of turbulence and clouds in cloud resolving models and general circulation models

    NASA Astrophysics Data System (ADS)

    Bogenschutz, Peter A.

    Over the past few years a new type of general circulation model (GCM) has emerged that is known as the multiscale modeling framework (MMF). The Colorado State University (CSU) MMF represents a coupling between the Community Atmosphere Model (CAM) GCM and the System of Atmospheric Modeling (SAM) cloud resolving model (CRM). Within this MMF the embedded CRM replaces the traditionally used parameterized moist physics in CAM to represent subgrid-scale (SGS) convection. However, due to substantial increases of computational burden associated with the MMF, the embedded CRM is typically run with a horizontal grid size of 4 km. With a horizontal grid size of 4 km, a low-order closure CRM cannot adequately represent shallow convective processes, such as trade-wind cumulus or stratocumulus. A computationally inexpensive parameterization of turbulence and clouds is presented in this dissertation. An extensive a priori test is performed to determine which functional form of an assumed PDF is best suited for coarse-grid CRMs for both deep shallow and deep convection. The diagnostic approach to determine the input moments needed for the assumed PDFs uses the subgrid-scale (SGS) turbulent kinetic energy (TKE) as the basis for the parameterization. The term known as the turbulent length scale (L) is examined, as it is needed to parameterize the dissipation of turbulence and therefore is needed to better balance the budgets of SGS TKE. A new formulation of this term is added to the model code which appears to be able to partition resolved and SGS TKE fairly accurately. Results from "offline" tests of the simple diagnostic closure within SAM shows that the cloud and turbulence properties of shallow convection can be adequately represented when compared to large eddy simulation (LES) benchmark simulations. Results are greatly improved when compared to the standard version of SAM. The preliminary test of the scheme within the embedded CRM of the MMF shows promising results with the

  16. Semi-automatic characterization of fractured rock masses using 3D point clouds: discontinuity orientation, spacing and SMR geomechanical classification

    NASA Astrophysics Data System (ADS)

    Riquelme, Adrian; Tomas, Roberto; Abellan, Antonio; Cano, Miguel; Jaboyedoff, Michel

    2015-04-01

    Investigation of fractured rock masses for different geological applications (e.g. fractured reservoir exploitation, rock slope instability, rock engineering, etc.) requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in 3D data acquisition using photogrammetric and/or LiDAR techniques currently allow a quick and an accurate characterization of rock mass discontinuities. This contribution presents a methodology for: (a) use of 3D point clouds for the identification and analysis of planar surfaces outcropping in a rocky slope; (b) calculation of the spacing between different discontinuity sets; (c) semi-automatic calculation of the parameters that play a capital role in the Slope Mass Rating geomechanical classification. As for the part a) (discontinuity orientation), our proposal identifies and defines the algebraic equations of the different discontinuity sets of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test. Additionally, the procedure finds principal orientations by Kernel Density Estimation and identifies clusters (Riquelme et al., 2014). As a result of this analysis, each point is classified with a discontinuity set and with an outcrop plane (cluster). Regarding the part b) (discontinuity spacing) our proposal utilises the previously classified point cloud to investigate how different outcropping planes are linked in space. Discontinuity spacing is calculated for each pair of linked clusters within the same discontinuity set, and then spacing values are analysed calculating their statistic values. Finally, as for the part c) the previous results are used to calculate parameters F_1, F2 and F3 of the Slope Mass Rating geomechanical classification. This analysis is carried out for each discontinuity set using their respective orientation extracted in part a). The open access tool SMRTool (Riquelme et al., 2014) is then used to calculate F1 to F3 correction

  17. Efficient data IO for a Parallel Global Cloud Resolving Model

    SciTech Connect

    Palmer, Bruce J.; Koontz, Annette S.; Schuchardt, Karen L.; Heikes, Ross P.; Randall, David A.

    2011-11-26

    Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk without creating a serious bottleneck in the execution of the GCRM code while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables modelers to easily add variables to the output stream by specifying where in the GCRM code these variables are located and to flexibly configure the choice of outputs and distribution of data across files. The flexibility of the API is designed to allow model developers to add new data fields to the output as the model develops and new physics is added and also provides a mechanism for allowing users of the GCRM code itself to adjust the output frequency and the number of fields written depending on the needs of individual calculations. Third, we describe the mapping to the NetCDF data model with an emphasis on the grid description. Fourth, we describe our messaging algorithms and IO aggregation strategies that are used to achieve high bandwidth while simultaneously writing concurrently from many processors to shared files. We conclude with initial performance results.

  18. Detection of Single Tree Stems in Forested Areas from High Density ALS Point Clouds Using 3d Shape Descriptors

    NASA Astrophysics Data System (ADS)

    Amiri, N.; Polewski, P.; Yao, W.; Krzystek, P.; Skidmore, A. K.

    2017-09-01

    Airborne Laser Scanning (ALS) is a widespread method for forest mapping and management purposes. While common ALS techniques provide valuable information about the forest canopy and intermediate layers, the point density near the ground may be poor due to dense overstory conditions. The current study highlights a new method for detecting stems of single trees in 3D point clouds obtained from high density ALS with a density of 300 points/m2. Compared to standard ALS data, due to lower flight height (150-200 m) this elevated point density leads to more laser reflections from tree stems. In this work, we propose a three-tiered method which works on the point, segment and object levels. First, for each point we calculate the likelihood that it belongs to a tree stem, derived from the radiometric and geometric features of its neighboring points. In the next step, we construct short stem segments based on high-probability stem points, and classify the segments by considering the distribution of points around them as well as their spatial orientation, which encodes the prior knowledge that trees are mainly vertically aligned due to gravity. Finally, we apply hierarchical clustering on the positively classified segments to obtain point sets corresponding to single stems, and perform ℓ1-based orthogonal distance regression to robustly fit lines through each stem point set. The ℓ1-based method is less sensitive to outliers compared to the least square approaches. From the fitted lines, the planimetric tree positions can then be derived. Experiments were performed on two plots from the Hochficht forest in Oberösterreich region located in Austria.We marked a total of 196 reference stems in the point clouds of both plots by visual interpretation. The evaluation of the automatically detected stems showed a classification precision of 0.86 and 0.85, respectively for Plot 1 and 2, with recall values of 0.7 and 0.67.

  19. Importance of the subgrid-scale turbulent moist process: Cloud distribution in global cloud-resolving simulations

    NASA Astrophysics Data System (ADS)

    Noda, Akira T.; Oouchi, Kazuyoshi; Satoh, Masaki; Tomita, Hirofumi; Iga, Shin-ichi; Tsushima, Yoko

    2010-05-01

    This study investigated the turbulent transport process within the nonhydrostatic icosahedral atmospheric model (NICAM), a global cloud-resolving model (GCRM), with particular focus on the spatial reproducibility of cloud characteristics in NICAM simulations. A turbulent closure model was applied, based on level 2 of the model developed by Nakanishi and Niino ([Nakanishi, M., and Niino, H., 2006: An improved Mellor-Yamada level-3 model: its numerical stability and application to a regional prediction of advection fog. Boundary-Layer Meteorol., 119, 397-407.]; a revised version of the original Mellor-Yamada model), together with a subgrid-scale condensation process. NICAM simulations were conducted for boreal summer of 2004 using mesh sizes of about 14 km and 7 km. Simulated cloud amounts and radiative budget were compared with observed data. The results confirmed an improvement in the spatial distribution of low clouds that develop in offshore regions of subtropical continents compared to past NICAM experiments ([Iga, S., Tomita, H., Tsushima, Y., and Satoh, M., 2007: Climatology of a nonhydrostatic global model with explicit cloud process. Geophys. Res. Lett., 34, L22814, doi:10.1029/2007/GL031048.]). A sensitivity study of subgrid-scale clouds in the turbulent closure scheme revealed that the turbulent transport process modulated by the subgrid-scale cloud strongly controls not only the low-cloud amount but also mid- and high-cloud amounts. This indicates that parameterization of unresolvable subgrid-scale clouds remains an important component of cloud behavior in GCRMs.

  20. Various Numerical Applications on Tropical Convective Systems Using a Cloud Resolving Model

    NASA Technical Reports Server (NTRS)

    Shie, C.-L.; Tao, W.-K.; Simpson, J.

    2003-01-01

    model. The modeled cloud generated from such an approach is termed continuously forced convection or continuous large-scale forced convection. A third study, which focuses on the respective impact of atmospheric components on upper Ocean heat and salt budgets, will be presented in the end. Unlike the two previous 2-D studies, this study employs the 3-D GCE-simulated diabatic source terms (using TOGA COARE observations) - radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the Ocean mixed-layer (OML) model.

  1. Various Numerical Applications on Tropical Convective Systems Using a Cloud Resolving Model

    NASA Technical Reports Server (NTRS)

    Shie, C.-L.; Tao, W.-K.; Simpson, J.

    2003-01-01

    model. The modeled cloud generated from such an approach is termed continuously forced convection or continuous large-scale forced convection. A third study, which focuses on the respective impact of atmospheric components on upper Ocean heat and salt budgets, will be presented in the end. Unlike the two previous 2-D studies, this study employs the 3-D GCE-simulated diabatic source terms (using TOGA COARE observations) - radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the Ocean mixed-layer (OML) model.

  2. Evaluation and improvement of the cloud resolving model component of the multi-scale modeling framework

    SciTech Connect

    Xu, Kuan-Man; Cheng, Anning

    2009-10-01

    Developed, implemented and tested an improved Colorado State University (CSU) SAM (System for Atmospheric Modeling) cloud-resolving model (CRM) with the advanced third-order turbulence closure (IPHOC).

  3. Global Tranport of Radon and Methyl iodide in a Cloud-Resolving Global Climate Model

    NASA Astrophysics Data System (ADS)

    Rosa, D.; Collins, W.; Lamarque, J.

    2011-12-01

    The global transport of the surface-emitted short-lived passive tracers radon and methyl iodide is simulated in a cloud-resolving global climate model (GCM) and in a conventional GCM in which cloud processes are not resolved. Simulated vertical profiles of tracers concentrations from both models are compared to profiles observed in situ. The comparisons suggest that the cloud-resolving GCM is better than the conventional GCM in reproducing the vertical gradients and hence the convective entrainment and detrainment of passive tracers. Contrasting climatological maps of tracers concentrations from simulations we find consistent and appreciable relative differences between the cloud-resolving GCM and the conventional case that might have important implications for climate and atmospheric chemistry simulations but require further investigations.

  4. 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.

  5. Detecting and Analyzing Corrosion Spots on the Hull of Large Marine Vessels Using Colored 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Aijazi, A. K.; Malaterre, L.; Tazir, M. L.; Trassoudaine, L.; Checchin, P.

    2016-06-01

    This work presents a new method that automatically detects and analyzes surface defects such as corrosion spots of different shapes and sizes, on large ship hulls. In the proposed method several scans from different positions and viewing angles around the ship are registered together to form a complete 3D point cloud. The R, G, B values associated with each scan, obtained with the help of an integrated camera are converted into HSV space to separate out the illumination invariant color component from the intensity. Using this color component, different surface defects such as corrosion spots of different shapes and sizes are automatically detected, within a selected zone, using two different methods depending upon the level of corrosion/defects. The first method relies on a histogram based distribution whereas the second on adaptive thresholds. The detected corrosion spots are then analyzed and quantified to help better plan and estimate the cost of repair and maintenance. Results are evaluated on real data using different standard evaluation metrics to demonstrate the efficacy as well as the technical strength of the proposed method.

  6. Using DOE-ARM and Space-Based Assets to Assess the Quality of Air Force Weather 3D Cloud Analysis and Forecast Products

    NASA Astrophysics Data System (ADS)

    Nobis, T. E.

    2015-12-01

    Air Force Weather (AFW) has documented requirements for global cloud analysis and forecasting to support DoD missions around the world. To meet these needs, AFW utilizes a number of cloud products. Cloud analyses are constructed using 17 different near real time satellite sources. Products include analysis of the individual satellite transmissions at native satellite resolution and an hourly global merge of all 17 sources on a 24km grid. AFW has also recently started creation of a time delayed global cloud reanalysis to produce a 'best possible' analysis for climatology and verification purposes. Forecasted cloud products include global short-range cloud forecasts created using advection techniques as well as statistically post processed cloud forecast products derived from various global and regional numerical weather forecast models. All of these cloud products cover different spatial and temporal resolutions and are produced on a number of different grid projections. The longer term vision of AFW is to consolidate these various approaches into uniform global numerical weather modeling (NWM) system using advanced cloudy-data assimilation processes to construct the analysis and a licensed version of UKMO's Unified Model to produce the various cloud forecast products. In preparation for this evolution in cloud modeling support, AFW has started to aggressively benchmark the performance of their current capabilities. Cloud information collected from so called 'active' sensors on the ground at the DOE-ARM sites and from space by such instruments as CloudSat, CALIPSO and CATS are being utilized to characterize the performance of AFW products derived largely by passive means. The goal is to understand the performance of the 3D cloud analysis and forecast products of today to help shape the requirements and standards for the future NWM driven system.This presentation will present selected results from these benchmarking efforts and highlight insights and observations

  7. A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in

  8. A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular

  9. A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new

  10. A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in

  11. A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new

  12. A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2005-01-01

    Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  14. Dynamic mineral clouds on HD 189733b. II. Monte Carlo radiative transfer for 3D cloudy exoplanet atmospheres: combining scattering and emission spectra

    NASA Astrophysics Data System (ADS)

    Lee, G. K. H.; Wood, K.; Dobbs-Dixon, I.; Rice, A.; Helling, Ch.

    2017-05-01

    Context. As the 3D spatial properties of exoplanet atmospheres are being observed in increasing detail by current and new generations of telescopes, the modelling of the 3D scattering effects of cloud forming atmospheres with inhomogeneous opacity structures becomes increasingly important to interpret observational data. Aims: We model the scattering and emission properties of a simulated cloud forming, inhomogeneous opacity, hot Jupiter atmosphere of HD 189733b. We compare our results to available Hubble Space Telescope (HST) and Spitzer data and quantify the effects of 3D multiple scattering on observable properties of the atmosphere. We discuss potential observational properties of HD 189733b for the upcoming Transiting Exoplanet Survey Satellite (TESS) and CHaracterising ExOPlanet Satellite (CHEOPS) missions. Methods: We developed a Monte Carlo radiative transfer code and applied it to post-process output of our 3D radiative-hydrodynamic, cloud formation simulation of HD 189733b. We employed three variance reduction techniques, i.e. next event estimation, survival biasing, and composite emission biasing, to improve signal to noise of the output. For cloud particle scattering events, we constructed a log-normal area distribution from the 3D cloud formation radiative-hydrodynamic results, which is stochastically sampled in order to model the Rayleigh and Mie scattering behaviour of a mixture of grain sizes. Results: Stellar photon packets incident on the eastern dayside hemisphere show predominantly Rayleigh, single-scattering behaviour, while multiple scattering occurs on the western hemisphere. Combined scattered and thermal emitted light predictions are consistent with published HST and Spitzer secondary transit observations. Our model predictions are also consistent with geometric albedo constraints from optical wavelength ground-based polarimetry and HST B band measurements. We predict an apparent geometric albedo for HD 189733b of 0.205 and 0.229, in the

  15. Simulations of Midlatitude Frontal Clouds by Single-Column and Cloud-Resolving Models during the Atmospheric Radiation Measurement March 2000 Cloud Intensive Operational Period

    SciTech Connect

    Xie, Shaocheng; Zhang, Minghua; Branson, Mark; Cederwall, Richard T.; Del Genio, Anthony D.; Eitzen, Zachary A.; Ghan, Steven J.; Iacobellis, Sam F.; Johnson, Karen L.; Khairoutdinov, Marat; Klein, Stephen A.; Krueger, Steven K.; Lin, Wuyin; Lohmann, Ulrike; Miller, Mark A.; Randall, David A.; Somerville, Richard C.; Sud, Yogesh C.; Walker, Gregory K.; Wolf, Audrey; Wu, Xiaoqing; Xu, Kuan-Man; Yio, J. John; Zhang, Guang J.; Zhang, Junhua

    2005-03-25

    This study quantitatively evaluates the overall performance of 9 single column models (SCMs) and 4 cloud resolving models (CRMs) in simulating a strong midlatitude frontal cloud system taken from the Spring 2000 Cloud Intensive Observational Period at the ARM Southern Great Plains site. The evaluation data are an analysis product of Constrained Variational Analysis of the ARM-Observations and the cloud data collected from the ARM ground active remote sensors (i.e., cloud radar, lidar, and laser ceilometers) and satellite retrievals. Both the selected SCMs and CRMs can typically capture the bulk characteristics of the frontal system and the frontal precipitation. However, there are significant differences in detailed structures of the frontal clouds. Both CRMs and SCMs overestimate high thin cirrus clouds before the main frontal passage. This is likely caused by the application of grid-scale upward motion in the upper troposphere when in reality only cloud streaks exist in narrow region s of upward sub-grid scale motion. During the passage of a front with strong upward motion, CRMs underestimate middle and low clouds while SCMs overestimate clouds at the levels above 765 hPa. The underestimation in the CRMs is presumably due to the lack of organized stratiform processes that are replaced by convections in the models under strong forcing. The overestimation in the SCMs is likely related to the uniform application of grid-averaged cooling and moistening associated with strong upward motion. All CRMs and some SCMs also underestimated the middle clouds after the frontal passage. This could be related to the lack of organized mesoscale cyclonic advection of hydrometeors behind the moving cyclone. Some of the SCMs simulated more middle clouds after frontal passage due to the long lifetime of cloud ice or prognostic cloud amount in the models. There are also large differences in the model simulations of cloud condensates due to differences in parameterizations, however

  16. Time-resolved particle image velocimetry measurements of the 3D single-mode Richtmyer-Meshkov instability

    NASA Astrophysics Data System (ADS)

    Xu, Qian

    The Richtmyer-Meshkov Instability (RMI) (Commun. Pure Appl. Math 23, 297-319, 1960; Izv. Akad. Nauk. SSSR Maekh. Zhidk. Gaza. 4, 151-157, 1969) occurs due to an impulsive acceleration acting on a perturbed interface between two fluids of different densities. In the experiments presented in this thesis, single mode 3D RMI experiments are performed. An oscillating speaker generates a single mode sinusoidal initial perturbation at an interface of two gases, air and SF6. A Mach 1.19 shock wave accelerates the interface and generates the Richtmyer-Meshkov Instability. Both gases are seeded with propylene glycol particles which are illuminated by an Nd: YLF pulsed laser. Three high-speed video cameras record image sequences of the experiment. Particle Image Velocimetry (PIV) is applied to measure the velocity field. Measurements of the amplitude for both spike and bubble are obtained, from which the growth rate is measured. For both spike and bubble experiments, amplitude and growth rate match the linear stability theory at early time, but fall into a non-linear region with amplitude measurements lying between the modified 3D Sadot et al. model ( Phys. Rev. Lett. 80, 1654-1657, 1998) and the Zhang & Sohn model (Phys. Fluids 9. 1106-1124, 1997; Z. Angew. Math Phys 50. 1-46, 1990) at late time. Amplitude and growth rate curves are found to lie above the modified 3D Sadot et al. model and below Zhang & Sohn model for the spike experiments. Conversely, for the bubble experiments, both amplitude and growth rate curves lie above the Zhang & Sohn model, and below the modified 3D Sadot et al. model. Circulation is also calculated using the vorticity and velocity fields from the PIV measurements. The calculated circulation are approximately equal and found to grow with time, a result that differs from the modified Jacobs and Sheeley's circulation model (Phys. Fluids 8, 405-415, 1996).

  17. Super-resolved 3-D imaging of live cells' organelles from bright-field photon transmission micrographs.

    PubMed

    Rychtáriková, Renata; Náhlík, Tomáš; Shi, Kevin; Malakhova, Daria; Macháček, Petr; Smaha, Rebecca; Urban, Jan; Štys, Dalibor

    2017-03-18

    Current biological and medical research is aimed at obtaining a detailed spatiotemporal map of a live cell's interior to describe and predict cell's physiological state. We present here an algorithm for complete 3-D modelling of cellular structures from a z-stack of images obtained using label-free wide-field bright-field light-transmitted microscopy. The method visualizes 3-D objects with a volume equivalent to the area of a camera pixel multiplied by the z-height. The computation is based on finding pixels of unchanged intensities between two consecutive images of an object spread function. These pixels represent strongly light-diffracting, light-absorbing, or light-emitting objects. To accomplish this, variables derived from Rényi entropy are used to suppress camera noise. Using this algorithm, the detection limit of objects is only limited by the technical specifications of the microscope setup-we achieve the detection of objects of the size of one camera pixel. This method allows us to obtain 3-D reconstructions of cells from bright-field microscopy images that are comparable in quality to those from electron microscopy images.

  18. Resolving the 3D velocity field inside a Roughness Sublayer in a turbulent channel flow using HPIV

    NASA Astrophysics Data System (ADS)

    Talapatra, Siddharth; Katz, Joseph

    2010-11-01

    Microscopic holographic PIV is used to measure the 3D velocity field within the roughness sublayer of a turbulent channel flow at Reτ of 3400. Recording holograms through a rough surface is facilitated by matching the optical refractive index of the rough wall with that of the working fluid, a concentrated solution of NaI in water. The pyramidal roughness height is k=0.45mm, the sample volume size is 3.2x1.8x1.8mm^3, the long dimension being in the streamwise direction, and the wall-normal range is -0.333D grid to obtain vectors with a spacing of 60μm or 8.5 wall units. The data show that at y/k<0.5, there is a preferred channeling of the flow along paths that circumvent the pyramid crest lines. Planar vorticity distribution from different perspectives as well as 3D isosurfaces show that the near wall region is flooded by quasi-streamwise vortices that are aligned at shallow angles and have a typical streamwise extent of 1-2k.

  19. A Comparison of TWP-ICE Observational Data with Cloud-Resolving Model Results

    SciTech Connect

    Fridlind, A. M.; Ackerman, Andrew; Chaboureau, Jean-Pierre; Fan, Jiwen; Grabowski, Wojciech W.; Hill, A.; Jones, T. R.; Khaiyer, M. M.; Liu, G.; Minnis, Patrick; Morrison, H.; Nguyen, L.; Park, S.; Petch, Jon C.; Pinty, Jean-Pierre; Schumacher, Courtney; Shipway, Ben; Varble, A. C.; Wu, Xiaoqing; Xie, Shaocheng; Zhang, Minghua

    2012-03-13

    Observations made during the TWP-ICE campaign are used to drive and evaluate thirteen cloud-resolving model simulations with periodic lateral boundary conditions. The simulations employ 2D and 3D dynamics, one- and two-moment microphysics, several variations on large-scale forcing, and the use of observationally derived aerosol properties to prognose droplet numbers. When domain means are averaged over a 6-day active monsoon period, all simulations reproduce observed surface precipitation rate but not its structural distribution. Simulated fractional areas covered by convective and stratiform rain are uncorrelated with one another, and are both variably overpredicted by up to a factor of {approx}2. Stratiform area fractions are strongly anticorrelated with outgoing longwave radiation (OLR) but are negligibly correlated with ice water path (IWP), indicating that ice spatial distribution controls OLR more than mean IWP. Overpredictions of OLR tend to be accompanied by underpredictions of reflected shortwave radiation (RSR). When there are two simulations differing only in microphysics scheme or large-scale forcing, the one with smaller stratiform area tends to exhibit greater OLR and lesser RSR by similar amounts. After {approx}10 days, simulations reach a suppressed monsoon period with a wide range of mean precipitable water vapor, attributable in part to varying overprediction of cloud-modulated radiative flux divergence compared with observationally derived values. Differences across the simulation ensemble arise from multiple sources, including dynamics, microphysics, and radiation treatments. Close agreement of spatial and temporal averages with observations may not be expected, but the wide spreads of predicted stratiform fraction and anticorrelated OLR indicate a need for more rigorous observation-based evaluation of the underlying micro- and macrophysical properties of convective and stratiform structures.

  20. Visualization of CSF Flow with Time-resolved 3D MR Velocity Mapping in Aqueductal Stenosis Before and After Endoscopic Third Ventriculostomy : A Feasibility Study.

    PubMed

    Brandner, Sebastian; Buchfelder, Michael; Eyuepoglu, Ilker Y; Luecking, Hannes; Doerfler, Arnd; Stadlbauer, Andreas

    2016-08-08

    The aim of this study was to evaluate timed-resolved three-dimensional (3D) magnetic resonance (MR) velocity mapping as a method for investigation of cerebrospinal fluid (CSF) flow changes in patients with aqueductal stenosis (AS) treated by endoscopic third ventriculostomy (ETV). The MR velocity mapping was performed in 12 AS patients before and after ETV and in 10 healthy volunteers by using a 3-Tesla MR system. Time-resolved 3D MR velocity mapping data were acquired with a standard 3D phase contrast (PC) sequence with cardiac triggering. Values of mean (vmean) and maximum (vpeak) velocity were measured at several ventricular structures using dedicated software. Of the patients 11 showed a satisfactory clinical improvement after ETV, whereas one patient needed subsequent shunt implantation. All AS patients showed significant hypomotile CSF flow dynamics in the third ventricle when compared to healthy subjects before surgery (p < 0.05). In contrast, CSF flow velocity was increased within the Foramen of Monro in AS patients. After ETV, all AS patients showed a decrease of CSF flow dynamics within the third ventricle. Mean and peak CSF flow velocities through the ventriculostomy were 1.72 ± 0.59 cm/s (vmean) and 3.53 ± 0.79 cm/s (vpeak), respectively after ETV. The patient who needed shunt implantation after ETV had the lowest flow velocities through the ventriculostomy. This study demonstrates that timed-resolved 3D MR velocity mapping is a useful imaging investigation for diagnostics and follow-up in patients with AS. This new technique provides an insight into the physiological CSF flow changes related with AS and its treatment.

  1. A study of the diurnal cycle of moist convection over land using a cloud-system resolving model

    NASA Astrophysics Data System (ADS)

    Wu, Chien-Ming

    In the first part of the dissertation, we investigated the large-scale impact of cloud-scale interactions using a 2D cloud-system resolving model (CSRM) whose physics consists of three major components: cloud microphysics, radiation and turbulence. Experiments we have performed with the CSRM can be classified into three groups: CONTROL, MI (Mean Input) and MO (Mean Output) experiments. In MI experiments, the input to a selected physics subroutine is horizontally averaged at each call over the entire domain of the CSRM. These experiments, therefore, eliminate the cloud-scale horizontal modulation of the process in question from the beginning. In MO experiments, on the other hand, all calculations are performed on the cloud scale, but the output from a selected physics subroutine is horizontally averaged. These experiments, therefore, eliminate the local effects of the process in question on other cloud-scale processes. These experiments not only confirm the importance of cloud-scale interactions but also suggest the existence of a problem in formulating the overall effects of physical processes on averaged fields. In the second part of the dissertation, we assess the control mechanism for the transition from shallow to deep convection with the CSRM. By comparing with a 3-D CSRM under conditions taken from the Large-scale Biosphere Atmosphere (in the Amazon) field study, we show that the 2-D CSRM reasonably represents the main features evident in previous 3-D simulations. To extract the essence of the transition from shallow to deep convection, we idealize the case based on observations to isolate two control parameters, the free troposphere stability and the relative humidity. The systematic dependence of the development of convection on the stability and the humidity show that the concept of a convective transition is a meaningful one. A transition time can be defined to evaluate the relationship of the transition time on the free tropospheric humidity and the

  2. Hourly resolved cloud modification factors in the ultraviolet

    NASA Astrophysics Data System (ADS)

    Staiger, H.; den Outer, P. N.; Bais, A. F.; Feister, U.; Johnsen, B.; Vuilleumier, L.

    2008-05-01

    Cloud impacts on the transfer of ultraviolet (UV) radiation through the atmosphere can be assessed by using a cloud modification factor (CMF). CMF, which is based on total global solar irradiation (SOLCMF), has proved to be a solid basis to derive CMFs for the UV radiation (UVCMF). This is an advantage, because total global irradiance, the basis for SOLCMF, is frequently measured and forecasted by numerical weather prediction systems and includes all relevant effects for radiation transmission, such as cloud optical depth, different cloud layers, multiple reflection, as well as the distinct difference as to whether the solar disc is obscured by clouds or not. In the UV range clouds decrease the irradiance to a lesser extent than in the visible and infrared spectral range. Thus the relationship between CMFs for solar radiation and for UV-radiation is not straight forward, but will depend on whether, for example, the solar zenith angle (SZA) and wavelength band or action spectrum in the UV have been taken into consideration. Den Outer et al. provide a UVCMF algorithm on a daily basis, which accounts for these influences. It requires as input a daily SOLCMF and the SZA at noon. The calculation of SOLCMF uses the clear-sky algorithm of the European Solar Radiation Atlas to account for varying turbidity impacts. The algorithm's capability to derive hourly UVCMFs based on the SZA at the corresponding hour and its worldwide applicability is validated for erythemal UV using observational data retrieved from the databases of the COST-Action 726 on "Long-term changes and climatology of UV radiation over Europe" and the USDA UV-B Monitoring Program. The clear-sky part of the models has proved to be of good quality. Accumulated to daily doses it forms a tight cluster of points to the highest measured daily sums. All sky model performances for hourly resolution are shown to be comparable in accuracy with the well performing daily models of the COST-726 model intercomparison.

  3. Using cloud resolving model simulations of deep convection to inform cloud parameterizations in large-scale models

    SciTech Connect

    Klein, Stephen A.; Pincus, Robert; Xu, Kuan-man

    2003-06-23

    Cloud parameterizations in large-scale models struggle to address the significant non-linear effects of radiation and precipitation that arise from horizontal inhomogeneity in cloud properties at scales smaller than the grid box size of the large-scale models. Statistical cloud schemes provide an attractive framework to self-consistently predict the horizontal inhomogeneity in radiation and microphysics because the probability distribution function (PDF) of total water contained in the scheme can be used to calculate these non-linear effects. Statistical cloud schemes were originally developed for boundary layer studies so extending them to a global model with many different environments is not straightforward. For example, deep convection creates abundant cloudiness and yet little is known about how deep convection alters the PDF of total water or how to parameterize these impacts. These issues are explored with data from a 29 day simulation by a cloud resolving model (CRM) of the July 1997 ARM Intensive Observing Period at the Southern Great Plains site. The simulation is used to answer two questions: (a) how well can the beta distribution represent the PDFs of total water relative to saturation resolved by the CRM? (b) how can the effects of convection on the PDF be parameterized? In addition to answering these questions, additional sections more fully describe the proposed statistical cloud scheme and the CRM simulation and analysis methods.

  4. 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

  5. 3D radiative transfer effects in multi-angle/multispectral radio-polarimetric signals from a mixture of clouds and aerosols viewed by a non-imaging sensor

    NASA Astrophysics Data System (ADS)

    Davis, Anthony B.; Garay, Michael J.; Xu, Feng; Qu, Zheng; Emde, Claudia

    2013-09-01

    When observing a spatially complex mix of aerosols and clouds in a single relatively large field-of-view, nature entangles their signals non-linearly through polarized radiation transport processes that unfold in the 3D position and direction spaces. In contrast, any practical forward model in a retrieval algorithm will use only 1D vector radiative transfer (vRT) in a linear mixing technique. We assess the difference between the observed and predicted signals using synthetic data from a high-fidelity 3D vRT model with clouds generated using a Large Eddy Simulation model and an aerosol climatology. We find that this difference is signal—not noise—for the Aerosol Polarimetry Sensor (APS), an instrument developed by NASA. Moreover, the worst case scenario is also the most interesting case, namely, when the aerosol burden is large, hence hase the most impact on the cloud microphysics and dynamics. Based on our findings, we formulate a mitigation strategy for these unresolved cloud adjacency effects assuming that some spatial information is available about the structure of the clouds at higher resolution from "context" cameras, as was planned for NASA's ill-fated Glory mission that was to carry the APS but failed to reach orbit. Application to POLDER (POLarization and Directionality of Earth Reflectances) data from the period when PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) was in the A-train is briefly discussed.

  6. A review of our understanding of the aerosol-cloud interaction from the perspective of a bin resolved cloud scale modelling

    NASA Astrophysics Data System (ADS)

    Flossmann, Andrea I.; Wobrock, Wolfram

    2010-09-01

    This review compiles the main results obtained using a mesoscale cloud model with bin resolved cloud micophysics and aerosol particle scavenging, as developed by our group over the years and applied to the simulation of shallow and deep convective clouds. The main features of the model are reviewed in different dynamical frameworks covering parcel model dynamics, as well as 1.5D, 2D and 3D dynamics. The main findings are summarized to yield a digested presentation which completes the general understanding of cloud-aerosol interaction, as currently available from textbook knowledge. Furthermore, it should provide support for general cloud model development, as it will suggest potentially minor processes that might be neglected with respect to more important ones and can support development of parameterizations for air quality, chemical transport and climate models. Our work has shown that in order to analyse dedicated campaign results, the supersaturation field and the complex dynamics of the specific clouds needs to be reproduced. Only 3D dynamics represents the variation of the supersaturation over the entire cloud, the continuous nucleation and deactivation of hydrometeors, and the dependence upon initial particle size distribution and solubility. However, general statements on certain processes can be obtained also by simpler dynamics. In particular, we found: Nucleation incorporates about 90% of the initial aerosol particle mass inside the cloud drops. Collision and coalescence redistributes the scavenged aerosol particle mass in such a way that the particle mass follows the main water mass. Small drops are more polluted than larger ones, as pollutant mass mixing ratio decreases with drops size. Collision and coalescence mixes the chemical composition of the generated drops. Their complete evaporation will release processed particles that are mostly larger and more hygroscopic than the initial particles. An interstitial aerosol is left unactivated between the

  7. [An automatic extraction algorithm for individual tree crown projection area and volume based on 3D point cloud data].

    PubMed

    Xu, Wei-Heng; Feng, Zhong-Ke; Su, Zhi-Fang; Xu, Hui; Jiao, You-Quan; Deng, Ou

    2014-02-01

    fixed angles to estimate crown projections, and (2) different regular volume formula to simulate crown volume according to the tree crown shapes. Based on the high-resolution 3D LIDAR point cloud data of individual tree, tree crown structure was reconstructed at a high rate of speed with high accuracy, and crown projection and volume of individual tree were extracted by this automatical untouched method, which can provide a reference for tree crown structure studies and be worth to popularize in the field of precision forestry.

  8. Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

    Observed and projected trends in large scale wind speed over the oceans prompt the question: how might marine stratocumulus clouds and their radiative properties respond to future changes in large scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum, and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and stronger entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning - afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ⪆ 50 g m-2, long wave emissions are very insensitive to LWP. This leads to the more general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. We find furthermore that large scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment, and in part because circulation driven by shear from large scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large scale wind

  9. Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

    DOE PAGES

    Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu

    2016-05-12

    Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus clouds and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds over the course of a diurnal cycle, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and strongermore » entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning–afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ≳50 gm–2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. Here, we find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over from

  10. Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

    NASA Astrophysics Data System (ADS)

    Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu

    2016-05-01

    Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus clouds and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds over the course of a diurnal cycle, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and stronger entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning-afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ⪆ 50 g m-2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. We find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over from buoyancy

  11. Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction

    SciTech Connect

    Chiu, Jui-Yuan Christine

    2014-04-10

    This project focuses on cloud-radiation processes in a general three-dimensional cloud situation, with particular emphasis on cloud optical depth and effective particle size. The proposal has two main parts. Part one exploits the large number of new wavelengths offered by the Atmospheric Radiation Measurement (ARM) zenith-pointing ShortWave Spectrometer (SWS), to develop better retrievals not only of cloud optical depth but also of cloud particle size. We also take advantage of the SWS’ high sampling resolution to study the “twilight zone” around clouds where strong aerosol-cloud interactions are taking place. Part two involves continuing our cloud optical depth and cloud fraction retrieval research with ARM’s 2-channel narrow vield-of-view radiometer and sunphotometer instrument by, first, analyzing its data from the ARM Mobile Facility deployments, and second, making our algorithms part of ARM’s operational data processing.

  12. An Examination of Two Pathways to Tropical Cyclogenesis Occurring in Idealized Simulations with a Cloud-Resolving Numerical Model

    DTIC Science & Technology

    2012-01-01

    1 An Examination of Two Pathways to Tropical Cyclogenesis occurring in Idealized Simulations with a Cloud -Resolving Numerical Model M. E...to: Melville Nicholls Melville.Nicholls@colorado.edu 10 Abstract Simulations are conducted with a cloud -resolving numerical model to...Simulations with a Cloud -Resolving Numerical Model 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e

  13. Radially resolved simulations of collapsing pebble clouds in protoplanetary discs

    NASA Astrophysics Data System (ADS)

    Wahlberg Jansson, Karl; Johansen, Anders

    2017-07-01

    We study the collapse of pebble clouds with a statistical model to find the internal structure of comet-sized planetesimals. Pebble-pebble collisions occur during the collapse, and the outcome of these collisions affects the resulting structure of the planetesimal. We expand our previous models by allowing the individual pebble sub-clouds to contract at different rates and by including the effect of gas drag on the contraction speed and in energy dissipation. Our results yield comets that are porous pebble-piles with particle sizes varying with depth. In the surface layers, there is a mixture of primordial pebbles and pebble fragments. The interior, on the other hand, consists only of primordial pebbles with a narrower size distribution, yielding higher porosity there. Our results imply that the gas in the protoplanetary disc plays an important role in determining the radial distribution of pebble sizes and porosity inside planetesimals.

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  15. Uav-Based Acquisition of 3d Point Cloud - a Comparison of a Low-Cost Laser Scanner and Sfm-Tools

    NASA Astrophysics Data System (ADS)

    Mader, D.; Blaskow, R.; Westfeld, P.; Maas, H.-G.

    2015-08-01

    The Project ADFEX (Adaptive Federative 3D Exploration of Multi Robot System) pursues the goal to develop a time- and cost-efficient system for exploration and monitoring task of unknown areas or buildings. A fleet of unmanned aerial vehicles equipped with appropriate sensors (laser scanner, RGB camera, near infrared camera, thermal camera) were designed and built. A typical operational scenario may include the exploration of the object or area of investigation by an UAV equipped with a laser scanning range finder to generate a rough point cloud in real time to provide an overview of the object on a ground station as well as an obstacle map. The data about the object enables the path planning for the robot fleet. Subsequently, the object will be captured by a RGB camera mounted on the second flying robot for the generation of a dense and accurate 3D point cloud by using of structure from motion techniques. In addition, the detailed image data serves as basis for a visual damage detection on the investigated building. This paper focuses on our experience with use of a low-cost light-weight Hokuyo laser scanner onboard an UAV. The hardware components for laser scanner based 3D point cloud acquisition are discussed, problems are demonstrated and analyzed, and a quantitative analysis of the accuracy potential is shown as well as in comparison with structure from motion-tools presented.

  16. Statistical Analyses of Satellite Cloud Object Data from CERES. Part III; Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds

    NASA Technical Reports Server (NTRS)

    Luo, Yali; Xu, Kuan-Man; Wielicki, Bruce A.; Wong, Takmeng; Eitzen, Zachary A.

    2007-01-01

    The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium- and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Ni o) and March 2000 (weak La Ni a). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud top height while it overestimates the differences in the

  17. Highly Resolved Long-term 3D Hydrological Simulation of a Forested Catchment with Litter Layer and Fractured Bedrock

    NASA Astrophysics Data System (ADS)

    Fang, Z.; Bogena, H. R.; Kollet, S. J.; Vereecken, H.

    2014-12-01

    Soil water content plays a key role in the water and energy balance in soil, vegetation and atmosphere systems. According to Wood et al. (2011) there is a grand need to increase global-scale hyper-resolution water-energy-biogeochemistry land surface modelling capabilities. However, such a model scheme should also recognize the epistemic uncertainties, as well as the nonlinearity and hysteresis in its dynamics. Unfortunately, it is not clear how to parameterize hydrological processes as a function of scale and how to test deterministic models with regard to epistemic uncertainties. In this study, high resolution long-term simulations were conducted in the highly instrumented TERENO hydrological observatory, the Wüstebach catchment. Soil hydraulic parameters were derived using inverse modeling with the Hydrus-1D model using the global optimization scheme SCE-UA and soil moisture data from a wireless soil moisture sensor network. The estimated parameters were then used for 3D simulations using the integrated parallel simulation platform ParFlow-CLM. The simulated soil water content, as well as evapotranspiration and runoff, were compared with long-term field observations to illustrate how well the model was able to reproduce the water budget dynamics. With variable model setup scenarios in boundary conditions and anisotropy of hydraulic conductivity, we investigated how lateral flow processes above the underlying fractured bedrock affects the simulation results. Furthermore, we explored the importance of the litter layer and the heterogeneity of the forest soil in the simulation of flow processes and model performance. For the analysis of spatial patterns of simulated and observed soil water content we applied the method of empirical orthogonal function (EOF). The results suggest that strong anisotropy in the hydraulic conductivity may be the reason for the fast lateral flow observed in Wüstebach. Introduction of heterogeneity in the hydraulic properties in the

  18. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

    2005-01-01

    Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

  19. Estimation of convective entrainment properties from a cloud-resolving model simulation during TWP-ICE

    NASA Astrophysics Data System (ADS)

    Zhang, Guang J.; Wu, Xiaoqing; Zeng, Xiping; Mitovski, Toni

    2016-10-01

    The fractional entrainment rate in convective clouds is an important parameter in current convective parameterization schemes of climate models. In this paper, it is estimated using a 1-km-resolution cloud-resolving model (CRM) simulation of convective clouds from TWP-ICE (the Tropical Warm Pool-International Cloud Experiment). The clouds are divided into different types, characterized by cloud-top heights. The entrainment rates and moist static energy that is entrained or detrained are determined by analyzing the budget of moist static energy for each cloud type. Results show that the entrained air is a mixture of approximately equal amount of cloud air and environmental air, and the detrained air is a mixture of ~80 % of cloud air and 20 % of the air with saturation moist static energy at the environmental temperature. After taking into account the difference in moist static energy between the entrained air and the mean environment, the estimated fractional entrainment rate is much larger than those used in current convective parameterization schemes. High-resolution (100 m) large-eddy simulation of TWP-ICE convection was also analyzed to support the CRM results. It is shown that the characteristics of entrainment rates estimated using both the high-resolution data and CRM-resolution coarse-grained data are similar. For each cloud category, the entrainment rate is high near cloud base and top, but low in the middle of clouds. The entrainment rates are best fitted to the inverse of in-cloud vertical velocity by a second order polynomial.

  20. 3D localized 2D ultrafast J-resolved magnetic resonance spectroscopy: in vitro study on a 7 T imaging system.

    PubMed

    Roussel, T; Giraudeau, P; Ratiney, H; Akoka, S; Cavassila, S

    2012-02-01

    2D Magnetic Resonance Spectroscopy (MRS) is a well known tool for the analysis of complicated and overlapped MR spectra and was therefore originally used for structural analysis. It also presents a potential for biomedical applications as shown by an increasing number of works related to localized in vivo experiments. However, 2D MRS suffers from long acquisition times due to the necessary collection of numerous increments in the indirect dimension (t(1)). This paper presents the first 3D localized 2D ultrafast J-resolved MRS sequence, developed on a small animal imaging system, allowing the acquisition of a 3D localized 2D J-resolved MRS spectrum in a single scan. Sequence parameters were optimized regarding Signal-to-Noise ratio and spectral resolution. Sensitivity and spatial localization properties were characterized and discussed. An automatic post-processing method allowing the reduction of artifacts inherent to ultrafast excitation is also presented. This sequence offers an efficient signal localization and shows a great potential for in vivo dynamic spectroscopy.

  1. The Relative Abundances of Resolved 12CH2D2 and 13CH3D and Mechanisms Controlling Isotopic Bond Ordering in Abiotic and Biotic Methane Gases

    NASA Astrophysics Data System (ADS)

    Young, E. D.; Kohl, I. E.; Sherwood Lollar, B.; Etiope, G.; Rumble, D.; Li, S.; Haghnegahdar, M. A.; Schauble, E. A.; McCain, K.; Foustoukos, D.; Sutcliffe, C. N.; Warr, O.; Ballentine, C. J.; Onstott, T. C.; Hosgormez, H.; Neubeck, A.; Marques, J. M.; Perez-Rodriguez, I. M.; Rowe, A. R.; LaRowe, D.; Magnabosco, C.; Bryndzia, T.

    2016-12-01

    We report measurements of resolved 12CH2D2 and 13CH3D at natural abundances in a variety of methane gases produced naturally and in the laboratory. The ability to resolve 12CH2D2 from 13CH3D provides unprecedented insights into the origin and evolution of CH4. The results identify conditions under which either isotopic bond order disequilibrium or equilibrium are expected. Where equilibrium obtains, concordant Δ12CH2D2 and Δ13CH3D temperatures can be used reliably for thermometry. We find that concordant temperatures do not always match previous hypotheses based on indirect estimates of temperature of formation nor temperatures derived from CH4/H2 D/H exchange, underscoring the importance of reliable thermometry based on the CH4 molecules themselves. Where Δ12CH2D2 and Δ13CH3D values are inconsistent with thermodynamic equilibrium, temperatures of formation derived from these species are spurious. In such situations, while formation temperatures are unavailable, disequilibrium isotopologue ratios nonetheless provide important information about the formation mechanism of the gas and the presence or absence of multiple sources or sinks. In particular, disequilibrium isotopologue ratios may provide the means for differentiating between methane produced by abiotic synthesis versus biological processes. Deficits in 12CH2D2 compared with equilibrium values in CH4 gas made by surface-catalyzed abiotic reactions are so large as to point towards a quantum tunneling origin. Tunneling also accounts for the more moderate depletions in 13CH3D that accompany the low 12CH2D2 abundances produced by abiotic reactions. The tunneling signature of abiotic CH4 formation may prove to be an important tracer of abiotic methane formation, especially where it is preserved by dissolution of gas in cool hydrothermal systems (e.g., Mars). Isotopologue signatures of abiotic methane production can be erased by infiltration of microbial communities, and Δ12CH2D2 values are a key tracer of

  2. The relative abundances of resolved l2CH2D2 and 13CH3D and mechanisms controlling isotopic bond ordering in abiotic and biotic methane gases

    NASA Astrophysics Data System (ADS)

    Young, E. D.; Kohl, I. E.; Lollar, B. Sherwood; Etiope, G.; Rumble, D.; Li (李姝宁), S.; Haghnegahdar, M. A.; Schauble, E. A.; McCain, K. A.; Foustoukos, D. I.; Sutclife, C.; Warr, O.; Ballentine, C. J.; Onstott, T. C.; Hosgormez, H.; Neubeck, A.; Marques, J. M.; Pérez-Rodríguez, I.; Rowe, A. R.; LaRowe, D. E.; Magnabosco, C.; Yeung, L. Y.; Ash, J. L.; Bryndzia, L. T.

    2017-04-01

    We report measurements of resolved 12CH2D2 and 13CH3D at natural abundances in a variety of methane gases produced naturally and in the laboratory. The ability to resolve 12CH2D2 from 13CH3D provides unprecedented insights into the origin and evolution of CH4. The results identify conditions under which either isotopic bond order disequilibrium or equilibrium are expected. Where equilibrium obtains, concordant Δ12CH2D2 and Δ13CH3D temperatures can be used reliably for thermometry. We find that concordant temperatures do not always match previous hypotheses based on indirect estimates of temperature of formation nor temperatures derived from CH4/H2 D/H exchange, underscoring the importance of reliable thermometry based on the CH4 molecules themselves. Where Δ12CH2D2 and Δ13CH3D values are inconsistent with thermodynamic equilibrium, temperatures of formation derived from these species are spurious. In such situations, while formation temperatures are unavailable, disequilibrium isotopologue ratios nonetheless provide novel information about the formation mechanism of the gas and the presence or absence of multiple sources or sinks. In particular, disequilibrium isotopologue ratios may provide the means for differentiating between methane produced by abiotic synthesis vs. biological processes. Deficits in 12CH2D2 compared with equilibrium values in CH4 gas made by surface-catalyzed abiotic reactions are so large as to point towards a quantum tunneling origin. Tunneling also accounts for the more moderate depletions in 13CH3D that accompany the low 12CH2D2 abundances produced by abiotic reactions. The tunneling signature may prove to be an important tracer of abiotic methane formation, especially where it is preserved by dissolution of gas in cool hydrothermal systems (e.g., Mars). Isotopologue signatures of abiotic methane production can be erased by infiltration of microbial communities, and Δ12CH2D2 values are a key tracer of microbial recycling.

  3. Production of Lightning NO(x) and its Vertical Distribution Calculated from 3-D Cloud-scale Chemical Transport Model Simulations

    NASA Technical Reports Server (NTRS)

    Ott, Lesley; Pickering, Kenneth; Stenchikov, Georgiy; Allen, Dale; DeCaria, Alex; Ridley, Brian; Lin, Ruei-Fong; Lang, Steve; Tao, Wei-Kuo

    2009-01-01

    A 3-D cloud scale chemical transport model that includes a parameterized source of lightning NO(x), based on observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P(sub IC) and cloud-to-ground (P(sub CG)) flash is estimated by assuming various values of P(sub IC) and P(sub CG) for each storm and determining which production scenario yields NO(x) mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P(sub CG) value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P(sub IC) may be nearly equal to P(sub CG), which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO(x), after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO(x), remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a "C-shaped" profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO(x) mass may place too much mass neat the surface and too little in the middle troposphere.

  4. Jupiter's Deep Cloud Structure Revealed Using Keck Observations of Spectrally Resolved Line Shapes

    NASA Technical Reports Server (NTRS)

    Bjoraker, G. L.; Wong, M.H.; de Pater, I.; Adamkovics, M.

    2015-01-01

    Technique: We present a method to determine the pressure at which significant cloud opacity is present between 2 and 6 bars on Jupiter. We use: a) the strength of a Fraunhofer absorption line in a zone to determine the ratio of reflected sunlight to thermal emission, and b) pressure- broadened line profiles of deuterated methane (CH3D) at 4.66 meters to determine the location of clouds. We use radiative transfer models to constrain the altitude region of both the solar and thermal components of Jupiter's 5-meter spectrum. Results: For nearly all latitudes on Jupiter the thermal component is large enough to constrain the deep cloud structure even when upper clouds are present. We find that Hot Spots, belts, and high latitudes have broader line profiles than do zones. Radiative transfer models show that Hot Spots in the North and South Equatorial Belts (NEB, SEB) typically do not have opaque clouds at pressures greater than 2 bars. The South Tropical Zone (STZ) at 32 degrees South has an opaque cloud top between 4 and 5 bars. From thermochemical models this must be a water cloud. We measured the variation of the equivalent width of CH3D with latitude for comparison with Jupiter's belt-zone structure. We also constrained the vertical profile of H2O in an SEB Hot Spot and in the STZ. The Hot Spot is very dry for a probability less than 4.5 bars and then follows the H2O profile observed by the Galileo Probe. The STZ has a saturated H2O profile above its cloud top between 4 and 5 bars.

  5. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne

    2008-01-01

    Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds [NRC, 2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path [Twomey, 1977] and the "semi-direct" effect on cloud coverage [e.g., Ackerman et al ., 2001]." Enhanced aerosol concentrations can also suppress warm rain processes by producing a narrow droplet spectrum that inhibits collision and coalescence processes [e.g., Squires and Twomey, 1961; Warner and Twomey, 1967; Warner, 1968; Rosenfeld, 19991. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect [Albrecht, 1989], is even more complex, especially for mixed-phase convective clouds. Table 1 summarizes the key observational studies identifying the microphysical properties, cloud characteristics, thermodynamics and dynamics associated with cloud systems from high-aerosol continental environments. For example, atmospheric aerosol concentrations can influence cloud droplet size distributions, warm-rain process, cold-rain process, cloud-top height, the depth of the mixed phase region, and occurrence of lightning. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing an enhanced source of cloud condensation nuclei (CCN). Hypotheses have been developed to explain the effect of urban regions on convection and precipitation [van den Heever and Cotton, 2007 and Shepherd, 2005

  6. Cloud Feedbacks in Limited-Area and Near-Global Cloud-Resolving Simulations of an Aquaplanet in SAM

    NASA Astrophysics Data System (ADS)

    Narenpitak, Pornampai

    Global climate models (GCMs) with conventional cumulus parameterization produce a wide spread in cloud feedbacks due to uncertainty from low clouds. Cloud-resolving model (CRM) and large-eddy simulations (LES) can be used to explicitly calculate individual clouds and study cloud-climate responses. This study concentrates on feedbacks of different cloud regimes in ocean-only CRMs of fixed sea-surface temperature (SST), both with small-area and near-global domain sizes. The first part of the thesis focuses on improvement of stratocumulus simulations in a coarse-resolution CRM with a grid spacing of 250 x 250 x 20 m. Three approaches were implemented to help the model maintain stratocumulus liquid water path, but only one is found to be helpful: turning off the subgrid scalar diffusivity except at the surface. The model setup has been further tested for its predictability of cloud feedbacks in various dynamical regimes. The CRM shows some biases in simulating the deep convective clouds and shallow cumulus since the domain size is too small. But it is able to simulate stratocumulus and stratocumulus under cumulus well. The second part focuses on cloud feedbacks in a near-global aquaplanet CRM with fixed meridionally-varying SST, under three climate perturbations: a uniform 4 K SST increase, CO2 quadrupling, and both combined. The CRM has a horizontal resolution of 4 km with no cumulus parameterization. Its domain is a zonally periodic 20480 km-long tropical channel, spanning 46?S-N with rigid walls. It produces plausible mean distributions of clouds, rainfall and winds. After spin-up, 80 days are analyzed for the control and increased-SST simulations, and 40 days for those with quadrupled CO2 . The Intertropical Convergence Zone width and tropical cloud cover are not strongly affected by SST warming or CO2 increase, except for the expected upward shift in high clouds with warming, but both perturbations weaken the Hadley circulation. Increased SST induces a

  7. Velocity Measurement in Carotid Artery: Quantitative Comparison of Time-Resolved 3D Phase-Contrast MRI and Image-based Computational Fluid Dynamics

    PubMed Central

    Sarrami-Foroushani, Ali; Nasr Esfahany, Mohsen; Nasiraei Moghaddam, Abbas; Saligheh Rad, Hamidreza; Firouznia, Kavous; Shakiba, Madjid; Ghanaati, Hossein; Wilkinson, Iain David; Frangi, Alejandro Federico

    2015-01-01

    Background: Understanding hemodynamic environment in vessels is important for realizing the mechanisms leading to vascular pathologies. Objectives: Three-dimensional velocity vector field in carotid bifurcation is visualized using TR 3D phase-contrast magnetic resonance imaging (TR 3D PC MRI) and computational fluid dynamics (CFD). This study aimed to present a qualitative and quantitative comparison of the velocity vector field obtained by each technique. Subjects and Methods: MR imaging was performed on a 30-year old male normal subject. TR 3D PC MRI was performed on a 3 T scanner to measure velocity in carotid bifurcation. 3D anatomical model for CFD was created using images obtained from time-of-flight MR angiography. Velocity vector field in carotid bifurcation was predicted using CFD and PC MRI techniques. A statistical analysis was performed to assess the agreement between the two methods. Results: Although the main flow patterns were the same for the both techniques, CFD showed a greater resolution in mapping the secondary and circulating flows. Overall root mean square (RMS) errors for all the corresponding data points in PC MRI and CFD were 14.27% in peak systole and 12.91% in end diastole relative to maximum velocity measured at each cardiac phase. Bland-Altman plots showed a very good agreement between the two techniques. However, this study was not aimed to validate any of methods, instead, the consistency was assessed to accentuate the similarities and differences between Time-resolved PC MRI and CFD. Conclusion: Both techniques provided quantitatively consistent results of in vivo velocity vector fields in right internal carotid artery (RCA). PC MRI represented a good estimation of main flow patterns inside the vasculature, which seems to be acceptable for clinical use. However, limitations of each technique should be considered while interpreting results. PMID:26793288

  8. Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography

    PubMed Central

    Yousaf, Ufra; Hsiao, Albert; Cheng, Joseph Y.; Alley, Marcus T.; Lustig, Michael; Pauly, John M.; Vasanawala, Shreyas S.

    2015-01-01

    Background Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. Objective To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast enhanced MR angiography method for depicting abdominal arterial anatomy in young children. Materials and methods With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast enhanced MR angiography studies. An radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Results Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9–5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Conclusion Free-breathing spatiotemporally accelerated 3-D time-resolved contrast enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries for pediatric contrast enhanced MR angiography. PMID:26040509

  9. Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography.

    PubMed

    Zhang, Tao; Yousaf, Ufra; Hsiao, Albert; Cheng, Joseph Y; Alley, Marcus T; Lustig, Michael; Pauly, John M; Vasanawala, Shreyas S

    2015-10-01

    Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography method for depicting abdominal arterial anatomy in young children. With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast-enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast-enhanced MR angiography studies. A radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9-5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries in young children.

  10. Suppression of Arctic Air Formation by Cloud Radiative Effects in a Two-Dimensional Cloud Resolving Model

    NASA Astrophysics Data System (ADS)

    Cronin, T.; Li, H.

    2015-12-01

    To better understand equable paleoclimates, Arctic amplification of winter warming, and the high-latitude lapse-rate feedback, we investigate the process of Arctic air formation, wherein a high latitude maritime air mass is advected over land during polar night and strongly cooled from the surface up. We extend previous work done using a single-column model (Cronin and Tziperman, PNAS, in press) by performing two-dimensional idealized cloud-resolving simulations with the Weather Research and Forecasting (WRF) model. Quantitatively consistent with previous results, we find that as the initial atmospheric state is warmed, increases in low cloud amount reduce the average surface cooling over a 14-day period by roughly a degree for each degree of warming of the initial atmospheric state, with the feedback strength increasing with warming. This is primarily attributed to a monotonic increase in surface cloud radiative forcing of approximately 2 W m-2 for each degree that the initial atmospheric sounding is warmed. The use of a two-dimensional model as opposed to a single-column model shows that the lower-tropospheric cloud layer becomes more turbulent and dominated by cumulus clouds as the climate is warmed, yet the cloud fraction remains high owing to the continued prevalence of stratus and fog layers. These results are robust across a variety of cloud microphysics schemes and are not sensitive to the horizontal or vertical resolution of the model. We also explore the vertical structure and horizontal variability of the bulk horizontal flow, the sensitivity of the results to subsidence and atmospheric carbon dioxide concentration, and the contrasting roles of top-of-atmosphere and surface cloud radiative effects.

  11. Cloud-Resolving Model Intercomparison with the ARM Summer 1997 IOP Data

    SciTech Connect

    Xu, K-M; Johnson, D E; Tao, W-K; Krueger, S K; Khairoutdinov, M; Randall, D A; Donner, L J; Seman, C J; Petch, J C; Guichard, F; Cederwell, R T; Xie, S C; Yio, J J; Grabowski, W; Zhang, M-H

    2000-03-13

    The Atmospheric Radiation Measurement (ARM) Program's Single Column Model (SCM) working group conducted its intercomparison study of midlatitude summertime continental convection using the July 1995 Intensive Operational Period (IOP) data set (Ghan et al. 2000). Only one cloud-resolving model (CRM) participated in the study. On the other hand, several CRMs participated in the GEWEX (Global Energy and Water-cycle Experiment) Cloud System Study (GCSS) Working Group 4's intercomparison study of tropical deep convection (Krueger and Lazarus 1998; Redelsperger et al. 2000). Both groups decided to have a joint intercomparison project to maximize the resources and advance our understanding of midlatitude continental convection. This joint project compares the cloud-resolving and single-column simulations of summertime continental cumulus convection observed at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site during the ARM Summer 1997 IOP. This paper reports the findings and results of cloud-resolving simulations, while Cederwall et al. (2000) reports the SCM part of the project. Seven CRMs are participating in this project.

  12. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

    2004-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

  13. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

    2004-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

  14. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

    2004-01-01

    Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

  15. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

    2004-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

  16. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

    2004-01-01

    Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

  17. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

    2004-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

  18. Spaceborne cloud-profiling radar: instrument parameter optimization for resolving highly layered cloud structures

    NASA Astrophysics Data System (ADS)

    Lin, Chung-Chi; Tinel, Claire; Caillault, Karine; Testud, Jacques; Caubet, Eric

    2003-04-01

    EarthCARE, a candidate Earth Explorer Core mission of ESA, aims to improve our knowledge of the impact of clouds and aerosols on the Earth's radiative budget. The satellite will carry two nadir sounding active instruments: a Cloud Profiling Radar (CPR) and a backscatter lidar. In addition, a multispectral cloud-imager, a Fourier transform spectrometer and a broadband radiometer complement the payload. The objective of the present study was to optimize the parameters of the CPR for retrieving accurate radiative profiles for highly layered cloud structures. Realistic cloud scenarios taken from ground-based experiments have been used for simulating the radar response to cloud layers. A radar simulator was developed initially for one-dimensional simulation of the radar echos. The cloud microphysical properties were retrieved using a model as a function of the reflectivity factor and temperature, based on information from in-situ measurements. An extensive parametric analysis was performed for various vertical resolutions and sensitivities which have direct impacts on the radar design and necessary resources on-board the satellite. The analysis demonstrated that the proposed radar characteristics will meet the top-of-the-atmosphere radiative flux density estimation accuracy of 10 W/m2 as recommended by WCRP.

  19. Chapter 25: Cloud-Resolving Modeling: ARM and the GCSS Story

    NASA Technical Reports Server (NTRS)

    Krueger, Steven K.; Morrison, Hugh; Fridlind, Ann M.

    2016-01-01

    The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was created in 1992. As described by Browning et al., The focus of GCSS is on cloud systems spanning the mesoscale rather than on individual clouds. Observations from field programs will be used to develop and validate the cloud-resolving models, which in turn will be used as test-beds to develop the parameterizations for the large-scale models. The most important activities that GCSS promoted were the following: Identify key questions about cloud systems relating to parameterization issues and suggest approaches to address them, and Organize model intercomparison studies relevant to cloud parameterization. Four different cloud system types were chosen for GCSS to study: boundary layer, cirrus, frontal, and deep precipitating convective. A working group (WG) was formed for each of the cloud system types. The WGs organized model intercomparison studies and meetings to present results of the intercomparisons. The first such intercomparison study took place in 1994.

  20. Chapter 25: Cloud-Resolving Modeling: ARM and the GCSS Story

    NASA Technical Reports Server (NTRS)

    Krueger, Steven K.; Morrison, Hugh; Fridlind, Ann M.

    2016-01-01

    The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was created in 1992. As described by Browning et al., The focus of GCSS is on cloud systems spanning the mesoscale rather than on individual clouds. Observations from field programs will be used to develop and validate the cloud-resolving models, which in turn will be used as test-beds to develop the parameterizations for the large-scale models. The most important activities that GCSS promoted were the following: Identify key questions about cloud systems relating to parameterization issues and suggest approaches to address them, and Organize model intercomparison studies relevant to cloud parameterization. Four different cloud system types were chosen for GCSS to study: boundary layer, cirrus, frontal, and deep precipitating convective. A working group (WG) was formed for each of the cloud system types. The WGs organized model intercomparison studies and meetings to present results of the intercomparisons. The first such intercomparison study took place in 1994.

  1. Effect of Clouds on Optical Imaging of the Space Shuttle During the Ascent Phase: A Statistical Analysis Based on a 3D Model

    NASA Technical Reports Server (NTRS)

    Short, David A.; Lane, Robert E., Jr.; Winters, Katherine A.; Madura, John T.

    2004-01-01

    Clouds are highly effective in obscuring optical images of the Space Shuttle taken during its ascent by ground-based and airborne tracking cameras. Because the imagery is used for quick-look and post-flight engineering analysis, the Columbia Accident Investigation Board (CAIB) recommended the return-to-flight effort include an upgrade of the imaging system to enable it to obtain at least three useful views of the Shuttle from lift-off to at least solid rocket booster (SRB) separation (NASA 2003). The lifetimes of individual cloud elements capable of obscuring optical views of the Shuttle are typically 20 minutes or less. Therefore, accurately observing and forecasting cloud obscuration over an extended network of cameras poses an unprecedented challenge for the current state of observational and modeling techniques. In addition, even the best numerical simulations based on real observations will never reach "truth." In order to quantify the risk that clouds would obscure optical imagery of the Shuttle, a 3D model to calculate probabilistic risk was developed. The model was used to estimate the ability of a network of optical imaging cameras to obtain at least N simultaneous views of the Shuttle from lift-off to SRB separation in the presence of an idealized, randomized cloud field.

  2. Cloud-Resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter

    DTIC Science & Technology

    2009-07-01

    ensembles for probabilistic forecasts of hurricanes . 1. Introduction Landfalling hurricanes are among the deadliest and costliest natural hazards. Over...Cloud-Resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter FUQING...Doppler radar radial velocity observations for cloud-resolving hurricane analysis, initialization, and prediction with an ensemble Kalman filter (EnKF

  3. Registration of overlapping 3D point clouds using extracted line segments. (Polish Title: Rejestracja chmur punktów 3D w oparciu o wyodrębnione krawędzie)

    NASA Astrophysics Data System (ADS)

    Poręba, M.; Goulette, F.

    2014-12-01

    The registration of 3D point clouds collected from different scanner positions is necessary in order to avoid occlusions, ensure a full coverage of areas, and collect useful data for analyzing and documenting the surrounding environment. This procedure involves three main stages: 1) choosing appropriate features, which can be reliably extracted; 2) matching conjugate primitives; 3) estimating the transformation parameters. Currently, points and spheres are most frequently chosen as the registration features. However, due to limited point cloud resolution, proper identification and precise measurement of a common point within the overlapping laser data is almost impossible. One possible solution to this problem may be a registration process based on the Iterative Closest Point (ICP) algorithm or its variation. Alternatively, planar and linear feature-based registration techniques can also be applied. In this paper, we propose the use of line segments obtained from intersecting planes modelled within individual scans. Such primitives can be easily extracted even from low-density point clouds. Working with synthetic data, several existing line-based registration methods are evaluated according to their robustness to noise and the precision of the estimated transformation parameters. For the purpose of quantitative assessment, an accuracy criterion based on a modified Hausdorff distance is defined. Since an automated matching of segments is a challenging task that influences the correctness of the transformation parameters, a correspondence-finding algorithm is developed. The tests show that our matching algorithm provides a correct p airing with an accuracy of 99 % at least, and about 8% of omitted line pairs.

  4. Cloud-resolving regional climate modeling approach in decade-long simulations

    NASA Astrophysics Data System (ADS)

    Ban, Nikolina; Schmidli, Jürg; Schär, Christoph

    2014-05-01

    The uncertainties in current global and regional climate model integrations are partly related to the representation of clouds, moist convection, and complex topography. Reducing the grid spacing down to some few kilometers and switching off the convection parameterization (cloud-resolving models) is thus an attractive approach. On climate time scales, cloud-resolving methods have been used for process studies, but application to long-term scenario simulations has been very limited. Here we present cloud-resolving simulations for 10-year-long periods integrated with the COSMO-CLM model and driven by reanalysis data (for present day climate) and a global climate model (control and scenario run). Two one-way nested grids are used with horizontal resolutions of 2.2 km for a cloud-resolving model (CRM) over an extended Alpine domain (1100 km x 1100 km), and 12 km for a cloud-parameterizing simulation (CPM) covering Europe. The CRM is driven by lateral boundary conditions from the CPM run, while the CPM run is driven by lateral boundary conditions from ERA-Interim reanalysis and the Earth-System Model of the Max-Planck-Institut (MPI-ESM-LR). Validation is conducted against high-resolution surface data. The CRM model strongly improves the simulation of the diurnal cycles of temperature and precipitation, while CPM has a poor diurnal cycle associated with the use of parameterized convection. The assessment of precipitation statistics reveals that both models adequately represent the frequency-intensity distribution for day-long events. For hourly events the CRM has a realistic representation of heavy precipitation events, while the CPM suffers from a strong underestimation. We also present results on the scaling of precipitation extremes with local daily-mean temperature and preliminary results on the projection of heavy precipitation events.

  5. Numerical 3D analysis of cloud cavitation shedding frequency on a circular leading edge hydrofoil with a barotropic cavitation model

    NASA Astrophysics Data System (ADS)

    Blume, M.; Skoda, R.

    2015-12-01

    A compressible density-based time-explicit low Mach number consistent viscous flow solver is utilised in combination with a barotropic cavitation model for the analysis of cloud cavitation on a circular leading edge (CLE) hydrofoil. For 5° angle of attack, cloud structure and shedding frequency for different cavitation numbers are compared to experimental data. A strong grid sensitivity is found in particular for high cavitation numbers. On a fine grid, a very good agreement with validation data is achieved even without explicit turbulence model. The neglect of viscous effects as well as a two-dimensional set-up lead to a less realistic prediction of cloud structures and frequencies. Comparative simulations with the Sauer-Schnerr cavitation model and modified pre-factors of the mass transfer terms underestimate the measured shedding frequency.

  6. Initial Self-Consistent 3D Electron-Cloud Simulations of the LHC Beam with the Code WARP+POSINST

    SciTech Connect

    Vay, J; Furman, M A; Cohen, R H; Friedman, A; Grote, D P

    2005-10-11

    We present initial results for the self-consistent beam-cloud dynamics simulations for a sample LHC beam, using a newly developed set of modeling capability based on a merge [1] of the three-dimensional parallel Particle-In-Cell (PIC) accelerator code WARP [2] and the electron-cloud code POSINST [3]. Although the storage ring model we use as a test bed to contain the beam is much simpler and shorter than the LHC, its lattice elements are realistically modeled, as is the beam and the electron cloud dynamics. The simulated mechanisms for generation and absorption of the electrons at the walls are based on previously validated models available in POSINST [3, 4].

  7. Simulations of the Atmospheric General Circulation Using a Cloud-Resolving Model as a Superparameterization of Physical Processes.

    NASA Astrophysics Data System (ADS)

    Khairoutdinov, Marat; Randall, David; Demott, Charlotte

    2005-07-01

    Traditionally, the effects of clouds in GCMs have been represented by semiempirical parameterizations. Recently, a cloud-resolving model (CRM) was embedded into each grid column of a realistic GCM, the NCAR Community Atmosphere Model (CAM), to serve as a superparameterization (SP) of clouds. Results of the standard CAM and the SP-CAM are contrasted, both using T42 resolution (2.8° × 2.8° grid), 26 vertical levels, and up to a 500-day-long simulation. The SP was based on a two-dimensional (2D) CRM with 64 grid columns and 24 levels collocated with the 24 lowest levels of CAM. In terms of the mean state, the SP-CAM produces quite reasonable geographical distributions of precipitation, precipitable water, top-of-the-atmosphere radiative fluxes, cloud radiative forcing, and high-cloud fraction for both December-January-February and June-July-August. The most notable and persistent precipitation bias in the western Pacific, during the Northern Hemisphere summer of all the SP-CAM runs with 2D SP, seems to go away through the use of a small-domain three-dimensional (3D) SP with the same number of grid columns as the 2D SP, but arranged in an 8 × 8 square with identical horizontal resolution of 4 km. Two runs with the 3D SP have been carried out, with and without explicit large-scale momentum transport by convection. Interestingly, the double ITCZ feature seems to go away in the run that includes momentum transport.The SP improves the diurnal variability of nondrizzle precipitation frequency over the standard model by precipitating most frequently during late afternoon hours over the land, as observed, while the standard model maximizes its precipitation frequency around local solar noon. Over the ocean, both models precipitate most frequently in the early morning hours as observed. The SP model also reproduces the observed global distribution of the percentage of days with nondrizzle precipitation rather well. In contrast, the standard model tends to precipitate more

  8. 3D point cloud data from laser scanning along the 2014 South Napa Earthquake surface rupture, California, USA

    USGS Publications Warehouse

    DeLong, Stephen B.

    2016-01-01

    Point cloud data collected along a 500 meter portion of the 2014 South Napa Earthquake surface rupture near Cuttings Wharf Road, Napa, CA, USA. The data include 7 point cloud files (.laz). The files are named with the location and date of collection and either ALSM for airborne laser scanner data or TLS for terrestrial laser scanner data. The ALSM data re previously released but are included here because they have been precisely aligned with the TLS data as described in the processing section of this metadata. 

  9. Resolved 12CH2D2 and 13CH3D in CH4 as Sensitive Indicators of Disequilibrium and Equilibrium during Microbial Methane Cycling

    NASA Astrophysics Data System (ADS)

    Ash, J. L.; Egger, M.; Slomp, C. P.; Kohl, I. E.; Treude, T.; Rumble, D.; Young, E. D.

    2016-12-01

    The ability to measure the relative concentrations of at least two doubly-substituted rare isotopologues of gases with biogeochemical relevance provides new constraints on sources and sinks of these gases. In particular, as shown recently for O2, the use of two independent, rare isotopologues allows for detection of thermodynamic intra-species equilibrium and disequilibrium. Here, we report the first measurements of fully resolved 13CH3D and 12CH2D2 from natural samples of microbial methane gas. A suite of sedimentary methane samples from the Bornholm Basin in the Baltic Sea was collected during IODP Exp. 347. Sample depths range from 2-20 meters below seafloor (mbsf). Methane concentrations decrease with depth, and mcrA (a marker for methanogenesis and methanotropy) is present throughout. See Figure. Both Δ13CH3D and Δ12CH2D2 increase with depth as methane concentrations decrease with the shallowest samples exhibiting disequilibrium by up to 2‰ in Δ13CH3D and 13‰ in Δ12CH2D2 while the deepest samples approach isotopic thermodynamic equilibrium (marked by grey bars in Figure). The Fe-mediated anaerobic oxidation of methane (Fe-AOM) has been inferred in these sediments by geochemical modeling . Slow methane cycling by methanogensis and methanotrophy is likely responsible for the approach to isotopic bond order equilibrium in CH4 with depth, consistent with Fe-AOM. While axenic culturing experiments generate methane with large deficits in 12CH2D2 (reported at this meeting), these data from the Baltic Sea demonstrate that isotopic equilibrium can be achieved during microbial recycling of methane. In the absence of Δ12CH2D2, the Δ13CH3D values alone could be misinterpreted as representing gradients in temperature due perhaps to exothermic organic matter degradation. The combination of both mass-18 rare isotopologues of methane provides the means to distinguish equilibrium from disequilibrium and probe microbial methane cycling even where Δ13CH3D suggests

  10. Spatially resolved 3D measurements of long-period gratings written by fs-laser inscription in large mode area fibers

    NASA Astrophysics Data System (ADS)

    Kliner, A.; Krämer, R. G.; Voigtländer, C.; Theuer, F.; Schreiber, T.; Eberhardt, R.; Nolte, S.; Tünnermann, A.

    2014-03-01

    High-power fiber lasers have reached kW power levels. The most important non-linear process limiting power scaling of industrial fiber lasers is stimulated Raman scattering. Long period gratings (LPGs) couple forward propagating core light to forward propagating cladding light and are well suited as a filter for the unwanted Raman scattering. In this paper we show for the first time of our knowledge the inscription of LPGs in large-mode-area (LMA) fibers with ultra-short laser pulses. We investigate the influence of different inscription parameters with a 3D, spatially resolved measurement of the induced index change. We present results from gratings with an attenuation of 8.5 dB at the desired wavelength with a small out-of-band loss of 1 dB.

  11. Spin-Orbit Effects in Spin-Resolved L2,3 Core Level Photoemission of 3d Ferromagnetic Thin Films

    SciTech Connect

    Komesu, T; Waddill, G D; Yu, S W; Butterfield, M; Tobin, J G

    2007-10-02

    We present spin-resolved 2p core level photoemission for the 3d transition metal films of Fe and Co grown on Cu(100). We observe clear spin asymmetry in the main 2p core level photoemission peaks of Fe and Co films consistent with trends in the bulk magnetic moments. The spin polarization can be strongly enhanced, by variation of the experimental geometry, when the photoemission is undertaken with circularly polarized light, indicating that spin-orbit interaction can have a profound in spin polarized photoemission. Further spin polarized photoemission studies using variable circularly polarized light at high photon energies, high flux are indicated, underscoring the value of synchrotron measurements at facilities with increased beam stability.

  12. Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds.

    PubMed

    Bae, Kwang-Ho

    2009-01-01

    Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larger rotational convergence region than the existing methods, e.g., the Iterative Closest Point (ICP).

  13. Evaluation of the Convergence Region of an Automated Registration Method for 3D Laser Scanner Point Clouds

    PubMed Central

    Bae, Kwang-Ho

    2009-01-01

    Using three dimensional point clouds from both simulated and real datasets from close and terrestrial laser scanners, the rotational and translational convergence regions of Geometric Primitive Iterative Closest Points (GP-ICP) are empirically evaluated. The results demonstrate the GP-ICP has a larger rotational convergence region than the existing methods, e.g., the Iterative Closest Point (ICP). PMID:22389603

  14. Momentum-resolved view of mixed 2D and nonbulklike 3D electronic structure of the surface state on SrTiO3 (001)

    NASA Astrophysics Data System (ADS)

    Plumb, N. C.; Salluzzo, M.; Razzoli, E.; Mansson, M.; Krempasky, J.; Matt, C. E.; Schmitt, T.; Shi, M.; Mesot, J.; Patthey, L.; Radovic, M.

    2014-03-01

    The recent discovery of a metallic surface state on SrTiO3 may open a route to simplified low-dimensional oxide-based conductors, as well as give new insights into interfacial phenomena in heterostructures such as LaAlO3/SrTiO3. Our recent angle-resolved photoemission spectroscopy (ARPES) study demonstrates that not only quasi-2D but also non-bulklike 3D Fermi surface components make up the surface state. Like their more 2D counterparts, the size and character of the 3D components are fixed with respect to a broad range of sample preparations. As seen in previous studies, the surface state can be ``prepared'' by photon irradiation under UHV conditions. An extremely high fraction of the surface valence states are affected by this process, especially in relation to the stability of oxygen core level intensity during the same exposure, which points to a key role of electronic/structural changes that spread over the surface as the metal emerges.

  15. The 3D flow structures generated by a pair of cubic roughness elements in a turbulent channel flow resolved using holographic microscopy

    NASA Astrophysics Data System (ADS)

    Gao, Jian; Katz, Joseph

    2015-11-01

    In studies of turbulent flows over rough walls, considerable efforts have been put on the overall effects of roughness parameters such as roughness height and spatial arrangement on the mean profiles and turbulence statistics. However there is very little experimental data on the generation, evolution, and interaction among roughness-initiated turbulent structures, which are essential for elucidating the near-wall turbulence production. As a first step, we approach this problem experimentally by applying digital holographic microscopy (DHM) to measure the flow and turbulence around a pair of cubic roughness elements embedded in the inner part of a high Reynolds number turbulent channel flow (Reτ = 2000 - 5000). The ratio of half-channel height (h) to cube height (a) is 25, and the cubes are aligned in the spanwise direction, and separated by 1.5 a. DHM provides high-resolution three-dimensional (3D) three-component (3C) velocity distributions. The presentation discusses methods to improve the data accuracy, both during the hologram acquisition and particle tracking phases. First, we compare and mutually validate velocity fields obtained from a two-view DHM system. Subsequently, during data processing, the seven criteria used for particle tracking is validated and augmented by planar tracking of particle image projections. Sample results reveal instantaneous 3D velocity fields and vortical structures resolved in fine details of several wall units. Funded by NSF and ONR.

  16. Joint Impact Proposal: A complete velocity resolved 3-D [CII] map of the M51 grand-design spiral galaxy: Unraveling the impact of spiral density waves on the evolution of the ISM and star formation.

    NASA Astrophysics Data System (ADS)

    Stutzki, Juergen

    2015-10-01

    We propose to obtain the first complete, velocity resolved [CII] 158um image of the M51 grand-design spiral galaxy with the upGREAT and FIFI-LS instruments on SOFIA. Spiral density waves play a fundamental role on the conversion of atomic to molecular gas, leading to gravitational contraction and thus to star formation. Understanding the impact of spiral density waves on the lifecycle of the interstellar medium and on star formation in galaxies is thus critical for our understanding of galaxy evolution. The [CII] line (in combination with the low-J CO lines and HI 21 cm) is an important tool to diagnose the physical state of the ISM. It can reveal the distribution of the gas that is making a transition between atomic and molecular phases, including the CO-dark H2 gas (hydrogen molecular but carbon ionized, and thus not traced by either HI or CO) in the spiral arms and interarm regions of M51. We will use the high spectral resolution of the upGREAT instrument to resolve spiral arms in velocity, allowing us to study the flow of gas through spiral arms and measure line widths and determine the dynamical state of prominent interarm clouds. The significantly more sensitive FIFI-LS will be used to detect extended faint [CII] emission in the interarm regions and outskirts of the galaxy, including the gas connection to the companion galaxy. The 3-D data cube of velocity-resolved [CII] in this nearby galaxy, combined with the wealth of ancillary data, can be used for a large set of investigations by the broader astronomical community. It will provide for the first time the link between the detailed physical processes in the star-forming ISM in the Milky Way and the average properties of distant external galaxies. This complete map will be also an excellent showcase of SOFIA's capabilities for years to come.

  17. Joint Impact Proposal: A complete velocity resolved 3-D [CII] map of the M51 grand-design spiral galaxy: Unraveling the impact of spiral density waves on the evolution of the ISM and star formation.

    NASA Astrophysics Data System (ADS)

    Pineda, Jorge

    2015-10-01

    We propose to obtain the first complete, velocity resolved [CII] 158um image of the M51 grand-design spiral galaxy with the upGREAT and FIFI-LS instruments on SOFIA. Spiral density waves play a fundamental role on the conversion of atomic to molecular gas, leading to gravitational contraction and thus to star formation. Understanding the impact of spiral density waves on the lifecycle of the interstellar medium and on star formation in galaxies is thus critical for our understanding of galaxy evolution. The [CII] line (in combination with the low-J CO lines and HI 21 cm) is an important tool to diagnose the physical state of the ISM. It can reveal the distribution of the gas that is making a transition between atomic and molecular phases, including the CO-dark H2 gas (hydrogen molecular but carbon ionized, and thus not traced by either HI or CO) in the spiral arms and interarm regions of M51. We will use the high spectral resolution of the upGREAT instrument to resolve spiral arms in velocity, allowing us to study the flow of gas through spiral arms and measure line widths and determine the dynamical state of prominent interarm clouds. The significantly more sensitive FIFI-LS will be used to detect extended faint [CII] emission in the interarm regions and outskirts of the galaxy, including the gas connection to the companion galaxy. The 3-D data cube of velocity--resolved [CII] in this nearby galaxy, combined with the wealth of ancillary data, can be used for a large set of investigations by the broader astronomical community. It will provide for the first time the link between the detailed physical processes in the star-forming ISM in the Milky Way and the average properties of distant external galaxies. This complete map will be also an excellent showcase of SOFIA's capabilities for years to come.

  18. Perturbed Physics Ensemble Simulations of Cirrus on the Cloud System-resolving Scale

    SciTech Connect

    Muhlbauer, Andreas; Berry, Elizabeth; Comstock, Jennifer M.; Mace, Gerald G.

    2014-04-16

    In this study, the effect of uncertainties in the parameterization of ice microphysical processes and initial conditions on the variability of cirrus microphysical and radiative properties are investigated in a series of cloud system-resolving perturbed physics ensemble (PPE) and initial condition ensemble (ICE) simulations. Three cirrus cases representative of mid-latitude, subtropical and tropical cirrus are examined. It is found that the variability in cirrus properties induced by perturbing uncertain parameters in ice microphysics parameterizations outweighs the variability induced by perturbing the initial conditions in midlatitude and subtropical cirrus. However, in tropical anvil cirrus the variability in the PPE and ICE simulations is about the same order of magnitude. The cirrus properties showing the largest sensitivity are ice water content (IWC) and cloud thickness whereas the averaged high cloud cover is only marginally affected. Changes in cirrus ice water path and outgoing longwave radiation are controlled primarily by changes in IWC and cloud thickness but not by changes is the averaged high cloud cover. The change in the vertical distribution of cloud fraction and cloud thickness is caused by changes in cirrus cloud base whereas cloud top is not sensitive to either perturbed physics or perturbed initial conditions. In all cirrus cases, the top three parameters controlling the microphysical variability and radiative impact of cirrus clouds are ice fall speeds, ice autoconversion size thresholds and heterogeneous ice nucleation. Changes in the ice deposition coefficient do not affect the ice water path and outgoing longwave radiation. Similarly, changes in the number concentration of aerosols available for homogeneous freezing have virtually no effect on the microphysical and radiative properties of midlatitude and subtropical cirrus but only little impact on tropical anvil cirrus. Overall, the sensitivity of cirrus microphysical and radiative

  19. Studies of 3D-cloud optical depth from small to very large values, and of the radiation and remote sensing impacts of larger-drop clustering

    SciTech Connect

    Wiscombe, Warren; Marshak, Alexander; Knyazikhin, Yuri; Chiu, Christine

    2007-05-04

    We have basically completed all the goals stated in the previous proposal and published or submitted journal papers thereon, the only exception being First-Principles Monte Carlo which has taken more time than expected. We finally finished the comprehensive book on 3D cloud radiative transfer (edited by Marshak and Davis and published by Springer), with many contributions by ARM scientists; this book was highlighted in the 2005 ARM Annual Report. We have also completed (for now) our pioneering work on new models of cloud drop clustering based on ARM aircraft FSSP data, with applications both to radiative transfer and to rainfall. This clustering work was highlighted in the FY07 “Our Changing Planet” (annual report of the US Climate Change Science Program). Our group published 22 papers, one book, and 5 chapters in that book, during this proposal period. All are listed at the end of this section. Below, we give brief highlights of some of those papers.

  20. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Khain, A.; Simpson, S.; Johnson, D.; Li, X.; Remer, L.

    2003-01-01

    Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low

  1. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Khain, A.; Simpson, S.; Johnson, D.; Li, X.; Remer, L.

    2003-01-01

    Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case

  2. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Khain, A.; Simpson, S.; Johnson, D.; Li, X.; Remer, L.

    2003-01-01

    Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case

  3. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Khain, A.; Simpson, S.; Johnson, D.; Li, X.; Remer, L.

    2003-01-01

    Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low

  4. Characterization of errors in cirrus simulations from a cloud resolving model for application in ice water content retrievals

    NASA Astrophysics Data System (ADS)

    Benedetti, A.; Stephens, G. L.

    Data available from the Atmospheric Radiation Measurement-Unmanned Aerospace Vehicle (ARM-UAV) Spring 1999 experiment are used in this study to estimate errors in cirrus simulations from a 3D Cloud Resolving Model (CRM). The performance of the model, heritage of the CSU Regional Atmospheric Modeling System (RAMS) is assessed by direct comparison of modeled and observed fields. Results show that the CRM succeeds in placing the cloud at approximately the correct altitude, but consistently overestimates the Ice Water Content (IWC). A statistical approach is introduced and applied to quantify average model bias under the assumption of bias-free observations. An error covariance matrix associated with simulated fields is also computed, and used to identify model strengths and deficiencies. Model fields are then used in the context of an optimum estimation retrieval of IWC from a combination of radar and radiometric observations. The retrieval is based on the knowledge of an a priori profile and relative error covariance to ensure algorithm convergence and stability. RAMS average Ice Water Content, corrected for the bias, and the related error covariance matrix derived in this study are used to provide this a priori information to the retrieval.

  5. Improving representation of convective transport for scale-aware parameterization: 2. Analysis of cloud-resolving model simulations

    NASA Astrophysics Data System (ADS)

    Liu, Yi-Chin; Fan, Jiwen; Zhang, Guang J.; Xu, Kuan-Man; Ghan, Steven J.

    2015-04-01

    Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the midlatitude continental and the tropical regions are conducted and evaluated, we examine the scale dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraft eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of midlatitude continental convection. We show that the single-updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as three updrafts can account for the internal variability of updrafts well. Based on the evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.

  6. Towards Realtime Assimilation of Doppler Radar Observations for Cloud-Resolving Hurricane Prediction

    NASA Astrophysics Data System (ADS)

    Weng, Y.; Zhang, F.; Gamache, J. F.; Marks, F. D.

    2008-12-01

    This study explores the feasibility and impacts of on-demand, real-time assimilation of Doppler radar observations straight from the planes with an ensemble Kalman filter (EnKF) to initialize a cloud-resolving hurricane prediction model. The NOAA P3 aircrafts have being flying into tropical cyclones to gather radar observations since 1994. These observations are significant in investigating and anglicizing hurricane's intensity, eye-wall structure and intensity changes, but the radar data has never been ingested into hurricane prediction models in real-time. Likely reasons are (1) insufficient model resolution due to inadequate computing resources for ingesting convective-scale details observed by the radar, (2) inadequacy of existing data assimilation method for operational models, and (3) lack of sufficient bandwidth in transmitting huge volume radar data to the ground in realtime. This work is built on our recent case studies of predicting the rapid formation and intensification of past hurricanes in assimilating both ground-base and/or airborne radial velocity into a cloud-resolving mesoscale model with EnKF. Under the auspices of NOAA Hurricane Forecasting Improvement Project (HFIP), we have access to the NSF-sponsored high-performance computing facility TACC at University of Texas at Austin that makes realtime cloud-resolving hurricane data assimilation and forecasting possible. We alleviate the requirement of large volume data transfer from the aircraft through developing a radar radial velocity data quality and thinning procedure (namely to produce superobervations or SOs) to significantly reduce the data size before being transferred. We have first conducted near realtime testing of the cloud-resolving data assimilation and forecasting with Weather Research and Forecast (WRF) model using 40.5, 13.5, 4.5 and 1.5 km grid spacings and movable nested grids for Hurricanes Dolly and Fay (2008). As of today, we have successfully demonstrated the feasibility, data

  7. Evaluation of Cloud-Resolving and Limited Area Model Intercomparison Simulations Using TWP-ICE Observations. Part 2 ; Precipitation Microphysics

    NASA Technical Reports Server (NTRS)

    Varble, Adam; Zipser, Edward J.; Fridland, Ann M.; Zhu, Ping; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; Shipway, Ben; Williams, Christopher

    2014-01-01

    Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (mu) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a mu of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing mu to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.

  8. Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 2: Rain Microphysics

    SciTech Connect

    Varble, Adam; Zipser, Edward J.; Fridlind, Ann; Zhu, Ping; Ackerman, Andrew; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; Shipway, Ben; Williams, Christopher R.

    2014-12-27

    Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, co-located UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain published results showing a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rain water contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (μ) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes, but lower RWCs than observed. Two moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and thus, may have issues balancing raindrop formation, collision coalescence, and raindrop breakup. Assuming a μ of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing μ to have values greater than 0 may improve two-moment schemes. Under-predicted stratiform rain rates are associated with under-predicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. In addition to stronger convective updrafts than observed, limited domain size prevents a large, well-developed stratiform region from developing in CRMs, while a dry bias in ECMWF analyses does the same to the LAMs.

  9. Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 2. Precipitation microphysics

    NASA Astrophysics Data System (ADS)

    Varble, Adam; Zipser, Edward J.; Fridlind, Ann M.; Zhu, Ping; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; Shipway, Ben; Williams, Christopher

    2014-12-01

    Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (μ) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a μ of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing μ to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.

  10. Evaluation of Cloud-Resolving and Limited Area Model Intercomparison Simulations Using TWP-ICE Observations. Part 2 ; Precipitation Microphysics

    NASA Technical Reports Server (NTRS)

    Varble, Adam; Zipser, Edward J.; Fridland, Ann M.; Zhu, Ping; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; Shipway, Ben; Williams, Christopher

    2014-01-01

    Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (mu) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a mu of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing mu to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.

  11. The Role of Atmospheric Aerosol Concentration on Deep Convective Precipitation: Cloud-resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.; Li, X.; Khain, A.; Mastsui, T.; Lang, S.; Simpson, J.

    2007-01-01

    Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 20011. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds NRC [2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path and the "semi-direct" effect on cloud coverage. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect, is even more complex, especially for mixed-phase convective clouds. ln this paper, a cloud-resolving model (CRM) with detailed spectral-bin microphysics was used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: South Florida, Oklahoma and the Central Pacific. In all three cases, rain reaches the ground earlier for the low CCN (clean) case. Rain suppression is also evident in all three cases with high CCN (dirty) case. However, this suppression only occurs during the first hour of the simulations. During the mature stages of the simulations, the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case, to almost no effect in the Florida case, to rain enhancement in the Pacific case. These results show the complexity of aerosol interactions with convection.

  12. Performance assessment of a triple-frequency spaceborne cloud-precipitation radar concept using a global cloud-resolving model

    NASA Astrophysics Data System (ADS)

    Leinonen, J.; Lebsock, M. D.; Tanelli, S.; Suzuki, K.; Yashiro, H.; Miyamoto, Y.

    2015-04-01

    Multi-frequency radars offer enhanced detection of clouds and precipitation compared to single-frequency systems, and are able to make more accurate retrievals when several frequencies are available simultaneously. An evaluation of a spaceborne three-frequency Ku/Ka/W-band radar system is presented in this study, based on modeling radar reflectivities from the results of a global cloud-resolving model with a 875 m grid spacing. To produce the reflectivities, a scattering model has been developed for each of the hydrometeor types produced by the model, as well as for melting snow. The effects of attenuation and multiple scattering on the radar signal are modeled using a radiative transfer model, while nonuniform beam filling is reproduced with spatial averaging. The combined effects of these are then quantified both globally and in five localized case studies. Two different orbital scenarios using the same radar are compared. Overall, based on the results, it is expected that the proposed radar would detect a high-quality signal in most clouds and precipitation. The main exceptions are the thinnest clouds that are below the detection threshold of the W-band channel, and at the opposite end of the scale, heavy convective rainfall where a combination of attenuation, multiple scattering and nonuniform beam filling commonly cause significant deterioration of the signal; thus, while the latter can be generally detected, the quality of the retrievals is likely to be degraded.

  13. Performance assessment of a triple-frequency spaceborne cloud-precipitation radar concept using a global cloud-resolving model

    NASA Astrophysics Data System (ADS)

    Leinonen, J.; Lebsock, M. D.; Tanelli, S.; Suzuki, K.; Yashiro, H.; Miyamoto, Y.

    2015-08-01

    Multi-frequency radars offer enhanced detection of clouds and precipitation compared to single-frequency systems, and are able to make more accurate retrievals when several frequencies are available simultaneously. An evaluation of a spaceborne three-frequency Ku-/Ka-/W-band radar system is presented in this study, based on modeling radar reflectivities from the results of a global cloud-resolving model with a 875 m grid spacing. To produce the reflectivities, a scattering model has been developed for each of the hydrometeor types produced by the model, as well as for melting snow. The effects of attenuation and multiple scattering on the radar signal are modeled using a radiative transfer model, while nonuniform beam filling is reproduced with spatial averaging. The combined effects of these are then quantified both globally and in six localized case studies. Two different orbital scenarios using the same radar are compared. Overall, based on the results, it is expected that the proposed radar would detect a high-quality signal in most clouds and precipitation. The main exceptions are the thinnest clouds that are below the detection threshold of the W-band channel, and at the opposite end of the scale, heavy convective rainfall where a combination of attenuation, multiple scattering and nonuniform beam filling commonly cause significant deterioration of the signal; thus, while the latter can be generally detected, the quality of the retrievals is likely to be degraded.

  14. Case studies of size resolved CCN composition and cloud properties in cumulus humilis

    NASA Astrophysics Data System (ADS)

    Yu, X.; Berg, L. K.; Berkowitz, C. M.; Lee, Y.; Alexander, L.; Ogren, J. A.; Andrews, B.

    2010-12-01

    The Cumulus Humilis Aerosol Processing Study (CHAPS) provided a unique opportunity to study cloud processing of aerosols. Clouds play an active role in the processing and cycling of atmosph