Investigation of Turbulent Entrainment-Mixing Processes With a New Particle-Resolved Direct Numerical Simulation Model

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

Gao, Zheng; Liu, Yangang; Li, Xiaolin

Here, a new particle-resolved three dimensional direct numerical simulation (DNS) model is developed that combines Lagrangian droplet tracking with the Eulerian field representation of turbulence near the Kolmogorov microscale. Six numerical experiments are performed to investigate the processes of entrainment of clear air and subsequent mixing with cloudy air and their interactions with cloud microphysics. The experiments are designed to represent different combinations of three configurations of initial cloudy area and two turbulence modes (decaying and forced turbulence). Five existing measures of microphysical homogeneous mixing degree are examined, modified, and compared in terms of their ability as a unifying measuremore » to represent the effect of various entrainment-mixing mechanisms on cloud microphysics. Also examined and compared are the conventional Damköhler number and transition scale number as a dynamical measure of different mixing mechanisms. Relationships between the various microphysical measures and dynamical measures are investigated in search for a unified parameterization of entrainment-mixing processes. The results show that even with the same cloud water fraction, the thermodynamic and microphysical properties are different, especially for the decaying cases. Further analysis confirms that despite the detailed differences in cloud properties among the six simulation scenarios, the variety of turbulent entrainment-mixing mechanisms can be reasonably represented with power-law relationships between the microphysical homogeneous mixing degrees and the dynamical measures.« less

Modelling operations and security of cloud systems using Z-notation and Chinese Wall security policy

NASA Astrophysics Data System (ADS)

Basu, Srijita; Sengupta, Anirban; Mazumdar, Chandan

2016-11-01

Enterprises are increasingly using cloud computing for hosting their applications. Availability of fast Internet and cheap bandwidth are causing greater number of people to use cloud-based services. This has the advantage of lower cost and minimum maintenance. However, ensuring security of user data and proper management of cloud infrastructure remain major areas of concern. Existing techniques are either too complex, or fail to properly represent the actual cloud scenario. This article presents a formal cloud model using the constructs of Z-notation. Principles of the Chinese Wall security policy have been applied to design secure cloud-specific operations. The proposed methodology will enable users to safely host their services, as well as process sensitive data, on cloud.

Forcing and Responses of the Surface Energy Budget at Summit, Greenland

NASA Astrophysics Data System (ADS)

Miller, Nathaniel B.

Energy exchange at the Greenland Ice Sheet surface governs surface temperature variability, a factor critical for representing increasing surface melt extent, which portends a rise in global sea level. A comprehensive set of cloud, tropospheric, near-surface and sub-surface measurements at Summit Station is utilized to determine the driving forces and subsequent responses of the surface energy budget (SEB). This budget includes radiative, turbulent, and ground heat fluxes, and ultimately controls the evolution of surface temperature. At Summit Station, clouds radiatively warm the surface in all months with an annual average cloud radiative forcing value of 33 W m -2, largely driven by the occurrence of liquid-bearing clouds. The magnitude of the surface temperature response is dependent on how turbulent and ground heat fluxes modulate changes to radiative forcing. Relationships between forcing terms and responding surface fluxes show that changes in the upwelling longwave radiation compensate for 65-85% (50- 60%) of the total change in radiative forcing in the winter (summer). The ground heat flux is the second largest response term (16% annually), especially during winter. Throughout the annual cycle, the sensible heat flux response is comparatively constant (9%) and latent heat flux response is only 1.5%, becoming more of a factor in modulating surface temperature responses during the summer. Combining annual cycles of these responses with cloud radiative forcing results, clouds warm the surface by an estimated 7.8°C annually. A reanalysis product (ERA-I), operational model (CFSv2), and climate model (CESM) are evaluated utilizing the comprehensive set of SEB observations and process-based relationships. Annually, surface temperatures in each model are warmer than observed with overall poor representation of the coldest surface temperatures. Process-based relationships between different SEB flux terms offer insight into how well a modeling framework represents physical processes and the ability to distinguish errors in forcing versus those in physical representation. Such relationships convey that all three models underestimate the response of surface temperatures to changes in radiative forcing. These results provide a method to expose model deficiencies and indicate the importance of representing surface, sub-surface and boundary-layer processes when portraying cloud impacts on surface temperature variability.

CHEMICAL HETEROGENEITY AMONG CLOUD DROP POPULATIONS AND ITS INFLUENCE ON AEROSOL PROCESSING IN WINTER CLOUDS. (R823979)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

THE INFLUENCE OF CHEMICAL HETEROGENEITY AMONG CLOUD DROP POPULATIONS ON AEROSOL PROCESSING IN WINTER CLOUDS. (R823979)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

THE INFLUENCE OF CHEMICAL HETEROGENEITY AMONG CLOUD DROP POPULATIONS ON AEROSOL PROCESSING IN WINTER CLOUDS. (U915364)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

RACORO Extended-Term Aircraft Observations of Boundary-Layer Clouds

NASA Technical Reports Server (NTRS)

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

Sensitivity simulations of superparameterised convection in a general circulation model

NASA Astrophysics Data System (ADS)

Rybka, Harald; Tost, Holger

2015-04-01

Cloud Resolving Models (CRMs) covering a horizontal grid spacing from a few hundred meters up to a few kilometers have been used to explicitly resolve small-scale and mesoscale processes. Special attention has been paid to realistically represent cloud dynamics and cloud microphysics involving cloud droplets, ice crystals, graupel and aerosols. The entire variety of physical processes on the small-scale interacts with the larger-scale circulation and has to be parameterised on the coarse grid of a general circulation model (GCM). Since more than a decade an approach to connect these two types of models which act on different scales has been developed to resolve cloud processes and their interactions with the large-scale flow. The concept is to use an ensemble of CRM grid cells in a 2D or 3D configuration in each grid cell of the GCM to explicitly represent small-scale processes avoiding the use of convection and large-scale cloud parameterisations which are a major source for uncertainties regarding clouds. The idea is commonly known as superparameterisation or cloud-resolving convection parameterisation. This study presents different simulations of an adapted Earth System Model (ESM) connected to a CRM which acts as a superparameterisation. Simulations have been performed with the ECHAM/MESSy atmospheric chemistry (EMAC) model comparing conventional GCM runs (including convection and large-scale cloud parameterisations) with the improved superparameterised EMAC (SP-EMAC) modeling one year with prescribed sea surface temperatures and sea ice content. The sensitivity of atmospheric temperature, precipiation patterns, cloud amount and types is observed changing the embedded CRM represenation (orientation, width, no. of CRM cells, 2D vs. 3D). Additionally, we also evaluate the radiation balance with the new model configuration, and systematically analyse the impact of tunable parameters on the radiation budget and hydrological cycle. Furthermore, the subgrid variability (individual CRM cell output) is analysed in order to illustrate the importance of a highly varying atmospheric structure inside a single GCM grid box. Finally, the convective transport of Radon is observed comparing different transport procedures and their influence on the vertical tracer distribution.

Characteristics of mid-level clouds over West Africa

NASA Astrophysics Data System (ADS)

Bourgeois, Elsa; Bouniol, Dominique; Couvreux, Fleur; Guichard, Françoise; Marsham, John; Garcia-Carreras, Luis; Birch, Cathryn; Parker, Doug

2017-04-01

Clouds have a major impact on the distribution of water and energy fluxes within the atmosphere. They also represent one of the main sources of uncertainties in global climate models as a result of the difficulty to parametrize cloud processes. However, in West Africa, the cloud type, occurrence and radiative effects have not been extensively documented. This region is characterized by a strong seasonality with precipitation occurring in the Sahel from June to September (monsoon season). This period also coincides with the annual maximum of the cloud cover. Taking advantage of the one-year ARM Mobile Facility (AMF) deployment in 2006 in Niamey (Niger), Bouniol et al (2012) documented the distinct cloud types and showed the frequent occurrence of mid-level clouds (around 6 km height) and their substantial impact on the surface short-wave and long-wave radiative fluxes. Furthermore, in a process-oriented evaluation of climate models, Roehrig et al (2013) showed that these mid-level clouds are poorly represented in numerical models. The aim of this work is to document the macro- and microphysical properties of mid-level clouds and the environment in which such clouds occur across West Africa. To document those clouds, we extensively make use of observations from lidar and cloud radar either deployed at ground-based sites (Niamey and Bordj Badji Mokhtar (Sahara)) or on-board the A-Train constellation (CloudSat/CALIPSO). These datasets reveal the temporal and spatial occurrence of those clouds. They are found throughout the year with a predominance around the monsoon season and are preferentially observed in the Southern and Western part of West Africa which could be linked to the dynamics of the Saharan heat low. Those clouds are usually quite thin (most of them are less than 1000m deep). A clustering method applied to this data allows us to identify three different types of clouds : one with low bases, one with high bases and another with large thicknesses. The first two clouds families are associated with potential temperature inversions at the top of the clouds. Complementary observations such as radiosondes and radiation measurements allow us to determine the thermodynamical stratification in which they occur as well as their radiative properties.

Theoretical studies in interstellar cloud chemistry

NASA Technical Reports Server (NTRS)

Chiu, Y. T.; Prasad, S. S.

1993-01-01

This final report represents the completion of the three tasks under the purchase order no. SCPDE5620,1,2F. Chemical composition of gravitationally contracting, but otherwise quiescent, interstellar clouds and of interstellar clouds traversed by high velocity shocks, were modeled in a comprehensive manner that represents a significant progress in modeling these objects. The evolutionary chemical modeling, done under this NASA contract, represents a notable advance over the 'classical' fixed condition equilibrium models because the evolutionary models consider not only the chemical processes but also the dynamical processes by which the dark interstellar clouds may have assumed their present state. The shock calculations, being reported here, are important because they extend the limited chemical composition derivable from dynamical calculations for the total density and temperature structures behind the shock front. In order to be tractable, the dynamical calculations must severely simplify the chemistry. The present shock calculations take the shock profiles from the dynamical calculations and derive chemical composition in a comprehensive manner. The results of the present modeling study are still to be analyzed with reference to astronomical observational data and other contemporary model predictions. As far as humanly possible, this analysis will be continued with CRE's (Creative Research Enterprises's) IR&D resources, until a sponsor is found.

Both sides now: the chemistry of clouds

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

Schwartz, S.E.

1984-01-01

Two complementary approaches to the study of the oxidation of SO/sub 2/ and NO/sub x/ to sulfuric and nitric acids as it occurs in liquid-water clouds are presented. The first approach relies upon laboratory determination of fundamental physical and chemical properties and evaluation of rates of dissolution and reaction for representative reagent concentrations and physical situations. The second approach consists of measuring concentrations of relevant reagent and product species and other pertinent quantities in and about clouds and of drawing inferences from these measurements about the rate and extent of processes responsible for establishing cloudwater composition. Based on laboratory studiesmore » the following inferences may be drawn: aqueous-phase oxidation of SO/sub 2/ by H/sub 2/O/sub 2/ or O/sub 3/ is sufficiently rapid to contribute to cloudwater acidity for representative concentrations of these oxidants; however, the rate of the O/sub 3/ reaction decreases strongly with decreasing pH and is of relatively little importance below about pH 4.5. Despite strong thermochemical driving force for oxidation of NO/sub 2/ to nitric acid in cloudwater, this reaction appears to be negligibly slow for representative concentrations of NO/sub 2/, largely because of the low Henry's law solubility of this species in water. These inferences gain support from field measurements of the composition of liquid water stratiform clouds at various locations in the eastern United States, which indicate that the fractional uptake of SO/sub 2/ (as SO/sub 4//sup =/) by cloudwater is frequently high, whereas a corresponding high fractional uptake of NO/sub x/ as NO/sub 3//sup -/ is never observed. A mutual exclusivity of gaseous SO/sub 2/ and dissolved H/sub 2/O/sub 2/ in clouds supports the inference that reaction of these species in clouds is rapid and represents a major process for cloudwater acidification. 143 references, 35 figures, 2 tables.« less

Formation of massive clouds and dwarf galaxies during tidal encounters

NASA Technical Reports Server (NTRS)

Kaufman, Michele; Elmegreen, Bruce G.; Thomasson, Magnus; Elmegreen, Debra M.

1993-01-01

Gerola et al. (1983) propose that isolated dwarf galaxies can form during galaxy interactions. As evidence of this process, Mirabel et al. (1991) find 10(exp 9) solar mass clouds and star formation complexes at the outer ends of the tidal arms in the Antennae and Superantennae galaxies. We describe observations of HI clouds with mass greater than 10(exp 8) solar mass in the interacting galaxy pair IC 2163/NGC 2207. This pair is important because we believe it represents an early stage in the formation of giant clouds during an encounter. We use a gravitational instability model to explain why the observed clouds are so massive and discuss a two-dimensional N-body simulation of an encounter that produces giant clouds.

The role of orbital dynamics and cloud-cloud collisions in the formation of giant molecular clouds in global spiral structures

NASA Technical Reports Server (NTRS)

Roberts, William W., Jr.; Stewart, Glen R.

1987-01-01

The role of orbit crowding and cloud-cloud collisions in the formation of GMCs and their organization in global spiral structure is investigated. Both N-body simulations of the cloud system and a detailed analysis of individual particle orbits are used to develop a conceptual understanding of how individual clouds participate in the collective density response. Detailed comparisons are made between a representative cloud-particle simulation in which the cloud particles collide inelastically with one another and give birth to and subsequently interact with young star associations and stripped down simulations in which the cloud particles are allowed to follow ballistic orbits in the absence of cloud-cloud collisions or any star formation processes. Orbit crowding is then related to the behavior of individual particle trajectories in the galactic potential field. The conceptual picture of how GMCs are formed in the clumpy ISMs of spiral galaxies is formulated, and the results are compared in detail with those published by other authors.

A-Train Based Observational Metrics for Model Evaluation in Extratropical Cyclones

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.; van den Heever, Susan C.; Posselt, Derek J.

2015-01-01

Extratropical cyclones contribute most of the precipitation in the midlatitudes, i.e. up to 70 during winter in the northern hemisphere, and can generate flooding, extreme winds, blizzards and have large socio-economic impacts. As such, it is important that general circulation models (GCMs) accurately represent these systems so their evolution in a warming climate can be understood. However, there are still uncertainties on whether warming will increase their frequency of occurrence, their intensity and how much rain or snow they bring. Part of the issue is that models have trouble representing their strength, but models also have biases in the amount of clouds and precipitation they produce. This is caused by potential issues in various aspects of the models: convection, boundary layer, and cloud scheme to only mention a few. In order to pinpoint which aspects of the models need improvement for a better representation of extratropical cyclone precipitation and cloudiness, we will present A-train based observational metrics: cyclone-centered, warm and cold frontal composites of cloud amount and type, precipitation rate and frequency of occurrence. Using the same method to extract similar fields from the model, we will present an evaluation of the GISS-ModelE2 and the IPSL-LMDZ-5B models, based on their AR5 and more recent versions. The AR5 version of the GISS model underestimates cloud cover in extratropical cyclones while the IPSL AR5 version overestimates it. In addition, we will show how the observed CloudSat-CALIPSO cloud vertical distribution across cold fronts changes with moisture amount and cyclone strength, and test if the two models successfully represent these changes. We will also show how CloudSat-CALIPSO derived cloud type (i.e. convective vs. stratiform) evolves across warm fronts as cyclones age, and again how this is represented in the models. Our third process-based analysis concerns cumulus clouds in the post-cold frontal region and how their amount relates to the stability of the boundary layer. This test uses Aqua cloud and vertical atmospheric profiles and when applied to the model output can help assess the accuracy of the convection, boundary layer and cloud scheme.

Observations of Co-variation in Cloud Properties and their Relationships with Atmospheric State

NASA Astrophysics Data System (ADS)

Sinclair, K.; van Diedenhoven, B.; Fridlind, A. M.; Arnold, T. G.; Yorks, J. E.; Heymsfield, G. M.; McFarquhar, G. M.; Um, J.

2017-12-01

Radiative properties of upper tropospheric ice clouds are generally not well represented in global and cloud models. Cloud top height, cloud thermodynamic phase, cloud optical thickness, cloud water path, particle size and ice crystal shape all serve as observational targets for models to constrain cloud properties. Trends or biases in these cloud properties could have profound effects on the climate since they affect cloud radiative properties. Better understanding of co-variation between these cloud properties and linkages with atmospheric state variables can lead to better representation of clouds in models by reducing biases in their micro- and macro-physical properties as well as their radiative properties. This will also enhance our general understanding of cloud processes. In this analysis we look at remote sensing, in situ and reanalysis data from the MODIS Airborne Simulator (MAS), Cloud Physics Lidar (CPL), Cloud Radar System (CRS), GEOS-5 reanalysis data and GOES imagery obtained during the Tropical Composition, Cloud and Climate Coupling (TC4) airborne campaign. The MAS, CPL and CRS were mounted on the ER-2 high-altitude aircraft during this campaign. In situ observations of ice size and shape were made aboard the DC8 and WB57 aircrafts. We explore how thermodynamic phase, ice effective radius, particle shape and radar reflectivity vary with altitude and also investigate how these observed cloud properties vary with cloud type, cloud top temperature, relative humidity and wind profiles. Observed systematic relationships are supported by physical interpretations of cloud processes and any unexpected differences are examined.

Chemical Processing of Organics within Clouds: Pilot Study at Whiteface Mountain in Upstate NY

NASA Astrophysics Data System (ADS)

Lance, S.; Carlton, A. G.; Barth, M. C.; Schwab, J. J.; Minder, J. R.; Freedman, J. M.; Zhang, J.; Brandt, R. E.; Casson, P.; Brewer, M.; Orlowski, D.; Christiansen, A.

2017-12-01

Aqueous chemical processing within cloud and fog water has been identified as a key process in the formation of secondary organic aerosol (SOA) mass, which is found abundantly throughout the troposphere. Yet, significant uncertainty remains regarding the organic chemical reactions taking place within clouds and the conditions under which those reactions occur. Routine longterm measurements from the Whiteface Mountain (WFM) Research Observatory in upstate NY provide a unique and broad view of regional air quality relevant to the formation of particulate matter within clouds, largely due to the fact that the summit of WFM is within non-precipitating clouds 30-50% in summertime and the site is undisturbed by local sources. An NSF-funded Cloud Chemistry Workshop in Sept 2016 brought together key researchers at WFM to lay out the most pertinent scientific questions relevant to heterogeneous chemistry occurring within fogs and clouds and to discuss preliminary model intercomparisons. The workshop culminated in a plan to coordinate chemical analyses of cloud water samples focused on chemical constituents thought to be most relevant for SOA formation. Workshop participants also recommended that a pilot study be conducted at WFM to better characterize the meteorological conditions, airflow patterns and clouds intercepting the site, in preparation for future intensive field operations focused on the chemical processing of organics within clouds. This presentation will highlight the experimental design and preliminary observations from the pilot study taking place at WFM in August 2017. Upwind below-cloud measurements of aerosol CCN activation efficiency, size distribution and chemical composition will be compared with similar measurements made at the summit. Under certain conditions, we anticipate that aerosols measured at the summit between cloud events will be representative of cloud droplet residuals recently detrained from the frequent shallow cumulus intercepting the summit. Wind LIDAR and radiosonde observations will be used to link the below-cloud and summit observations. These pre- and post- `cloud processed' aerosols will also be compared with the chemical composition of cloud water samples to evaluate changes to the organic partitioning in the aqueous and aerosol phases.

Lagrangian condensation microphysics with Twomey CCN activation

NASA Astrophysics Data System (ADS)

Grabowski, Wojciech W.; Dziekan, Piotr; Pawlowska, Hanna

2018-01-01

We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.

Applying super-droplets as a compact representation of warm-rain microphysics for aerosol-cloud-aerosol interactions

NASA Astrophysics Data System (ADS)

Arabas, S.; Jaruga, A.; Pawlowska, H.; Grabowski, W. W.

2012-12-01

Clouds may influence aerosol characteristics of their environment. The relevant processes include wet deposition (rainout or washout) and cloud condensation nuclei (CCN) recycling through evaporation of cloud droplets and drizzle drops. Recycled CCN physicochemical properties may be altered if the evaporated droplets go through collisional growth or irreversible chemical reactions (e.g. SO2 oxidation). The key challenge of representing these processes in a numerical cloud model stems from the need to track properties of activated CCN throughout the cloud lifecycle. Lack of such "memory" characterises the so-called bulk, multi-moment as well as bin representations of cloud microphysics. In this study we apply the particle-based scheme of Shima et al. 2009. Each modelled particle (aka super-droplet) is a numerical proxy for a multiplicity of real-world CCN, cloud, drizzle or rain particles of the same size, nucleus type,and position. Tracking cloud nucleus properties is an inherent feature of the particle-based frameworks, making them suitable for studying aerosol-cloud-aerosol interactions. The super-droplet scheme is furthermore characterized by linear scalability in the number of computational particles, and no numerical diffusion in the condensational and in the Monte-Carlo type collisional growth schemes. The presentation will focus on processing of aerosol by a drizzling stratocumulus deck. The simulations are carried out using a 2D kinematic framework and a VOCALS experiment inspired set-up (see http://www.rap.ucar.edu/~gthompsn/workshop2012/case1/).

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

NASA Technical Reports Server (NTRS)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Montmessin, F.; Brecht, A. S.; Urata, R.; Klassen, D. R.; Wolff, M. J.

2017-01-01

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Comparison of convective clouds observed by spaceborne W-band radar and simulated by cloud-resolving atmospheric models

NASA Astrophysics Data System (ADS)

Dodson, Jason B.

Deep convective clouds (DCCs) play an important role in regulating global climate through vertical mass flux, vertical water transport, and radiation. For general circulation models (GCMs) to simulate the global climate realistically, they must simulate DCCs realistically. GCMs have traditionally used cumulus parameterizations (CPs). Much recent research has shown that multiple persistent unrealistic behaviors in GCMs are related to limitations of CPs. Two alternatives to CPs exist: the global cloud-resolving model (GCRM), and the multiscale modeling framework (MMF). Both can directly simulate the coarser features of DCCs because of their multi-kilometer horizontal resolutions, and can simulate large-scale meteorological processes more realistically than GCMs. However, the question of realistic behavior of simulated DCCs remains. How closely do simulated DCCs resemble observed DCCs? In this study I examine the behavior of DCCs in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and Superparameterized Community Atmospheric Model (SP-CAM), the latter with both single-moment and double-moment microphysics. I place particular emphasis on the relationship between cloud vertical structure and convective environment. I also emphasize the transition between shallow clouds and mature DCCs. The spatial domains used are the tropical oceans and the contiguous United States (CONUS), the latter of which produces frequent vigorous convection during the summer. CloudSat is used to observe DCCs, and A-Train and reanalysis data are used to represent the large-scale environment in which the clouds form. The CloudSat cloud mask and radar reflectivity profiles for CONUS cumuliform clouds (defined as clouds with a base within the planetary boundary layer) during boreal summer are first averaged and compared. Both NICAM and SP-CAM greatly underestimate the vertical growth of cumuliform clouds. Then they are sorted by three large-scale environmental variables: total preciptable water (TPW), surface air temperature (SAT), and 500hPa vertical velocity (W500), representing the dynamical and thermodynamical environment in which the clouds form. The sorted CloudSat profiles are then compared with NICAM and SP-CAM profiles simulated with the Quickbeam CloudSat simulator. Both models have considerable difficulty representing the relationship of SAT and clouds over CONUS. For TPW and W500, shallow clouds transition to DCCs at higher values than observed. This may be an indication of the models' inability to represent the formation of DCCs in marginal convective environments. NICAM develops tall DCCs in highly favorable environments, but SP-CAM appears to be incapable of developing tall DCCs in almost any environment. The use of double moment microphysics in SP-CAM improves the frequency of deep clouds and their relationship with TPW, but not SAT. Both models underpredict radar reflectivity in the upper cloud of mature DCCs. SP-CAM with single moment microphysics has a particularly unrealistic DCC reflectivity profile, but with double moment microphysics it improves substantially. SP-CAM with double-moment microphysics unexpectedly appears to weaken DCC updraft strength as TPW increases, but otherwise both NICAM and SP-CAM represent the environment-versus-DCC relationships fairly realistically.

Evaluation of Cirrus Cloud Simulations using ARM Data-Development of Case Study Data Set

NASA Technical Reports Server (NTRS)

Starr, David OC.; Demoz, Belay; Wang, Yansen; Lin, Ruei-Fong; Lare, Andrew; Mace, Jay; Poellot, Michael; Sassen, Kenneth; Brown, Philip

2002-01-01

Cloud-resolving models (CRMs) are being increasingly used to develop parametric treatments of clouds and related processes for use in global climate models (GCMs). CRMs represent the integrated knowledge of the physical processes acting to determine cloud system lifecycle and are well matched to typical observational data in terms of physical parameters/measurables and scale-resolved physical processes. Thus, they are suitable for direct comparison to field observations for model validation and improvement. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. The objective is to compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. Progress is assessing cloud and other environmental conditions will be described. Results of preliminary simulations using a regional cloud system model (MM5) and a CRM will be discussed. Focal science questions for the model comparison are strongly based on results of the idealized GCSS WG2 cirrus cloud model comparison projects (Idealized Cirrus Cloud Model Comparison Project and Cirrus Parcel Model Comparison Project), which will also be briefly summarized.

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.

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

NASA Astrophysics Data System (ADS)

McFarquhar, G. M.

2016-12-01

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

Knowledge-Based Object Detection in Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Boochs, F.; Karmacharya, A.; Marbs, A.

2012-07-01

Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

'Cloud computing' and clinical trials: report from an ECRIN workshop.

PubMed

Ohmann, Christian; Canham, Steve; Danielyan, Edgar; Robertshaw, Steve; Legré, Yannick; Clivio, Luca; Demotes, Jacques

2015-07-29

Growing use of cloud computing in clinical trials prompted the European Clinical Research Infrastructures Network, a European non-profit organisation established to support multinational clinical research, to organise a one-day workshop on the topic to clarify potential benefits and risks. The issues that arose in that workshop are summarised and include the following: the nature of cloud computing and the cloud computing industry; the risks in using cloud computing services now; the lack of explicit guidance on this subject, both generally and with reference to clinical trials; and some possible ways of reducing risks. There was particular interest in developing and using a European 'community cloud' specifically for academic clinical trial data. It was recognised that the day-long workshop was only the start of an ongoing process. Future discussion needs to include clarification of trial-specific regulatory requirements for cloud computing and involve representatives from the relevant regulatory bodies.

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

Structure and covariance of cloud and rain water in marine stratocumulus

NASA Astrophysics Data System (ADS)

Witte, Mikael; Morrison, Hugh; Gettelman, Andrew

2017-04-01

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

Large-eddy simulation of subtropical cloud-topped boundary layers: 1. A forcing framework with closed surface energy balance

NASA Astrophysics Data System (ADS)

Tan, Zhihong; Schneider, Tapio; Teixeira, João.; Pressel, Kyle G.

2016-12-01

Large-eddy simulation (LES) of clouds has the potential to resolve a central question in climate dynamics, namely, how subtropical marine boundary layer (MBL) clouds respond to global warming. However, large-scale processes need to be prescribed or represented parameterically in the limited-area LES domains. It is important that the representation of large-scale processes satisfies constraints such as a closed energy balance in a manner that is realizable under climate change. For example, LES with fixed sea surface temperatures usually do not close the surface energy balance, potentially leading to spurious surface fluxes and cloud responses to climate change. Here a framework of forcing LES of subtropical MBL clouds is presented that enforces a closed surface energy balance by coupling atmospheric LES to an ocean mixed layer with a sea surface temperature (SST) that depends on radiative fluxes and sensible and latent heat fluxes at the surface. A variety of subtropical MBL cloud regimes (stratocumulus, cumulus, and stratocumulus over cumulus) are simulated successfully within this framework. However, unlike in conventional frameworks with fixed SST, feedbacks between cloud cover and SST arise, which can lead to sudden transitions between cloud regimes (e.g., stratocumulus to cumulus) as forcing parameters are varied. The simulations validate this framework for studies of MBL clouds and establish its usefulness for studies of how the clouds respond to climate change.

The pH and ionic composition of stratiform cloud water

NASA Astrophysics Data System (ADS)

Castillo, Raymond A.; Jiusto, James E.; Mclaren, Eugene

Over 50 cloud water samples were collected during five comprehensive case studies of the water chemistry of stratiform clouds at Whiteface Mountain, New York. The water samples were analyzed for pH, conductivity and ions of sodium, potassium, magnesium, calcium, ammonium, sulfate, chloride and nitrate. Trajectory analyses and cloud condensation nucleus concentrations at 0.5 % confirmed that the air masses in all five of these cases represented continental air that was relatively clean (low aerosol concentration) for the northeystern United States. The major ions related to cloud water pH were found to be sulfate, nitrate, potassium, ammonium and calcium. The results revealed a mean hydrogen ion concentration [ H+] = 0.239 meq ℓ -1 ( σ = ± 0.21) which converts to a mean pH = 3.6 for all collected cloud samples. The low pH values are related to a normal background of nitrate ions found in the rural continental air masses plus sulfate ions largely from the industrial emissions of the midwestern United States. The [NO -3], in two of the three cases presented, demonstrates the importance of the nitrate ions' contribution to the pH of cloud water. A dependent means analysis of 40 events yielded a significant difference (0.04 level of significance), with the mean pH of precipitation (4.2) being greater than the mean pH of cloud water (4.0) for event samples. The ion concentrations indicated that the cloud rainout process contributed from 67 % to almost 100% of the total ion concentration of the precipitation. The washout process, i.e. precipitation scavenging below the cloud base, contributed considerably less than the cloud/rainout process of those total precipitation anions associated with air pollution.

An adaptive process-based cloud infrastructure for space situational awareness applications

NASA Astrophysics Data System (ADS)

Liu, Bingwei; Chen, Yu; Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik; Rubin, Bruce

2014-06-01

Space situational awareness (SSA) and defense space control capabilities are top priorities for groups that own or operate man-made spacecraft. Also, with the growing amount of space debris, there is an increase in demand for contextual understanding that necessitates the capability of collecting and processing a vast amount sensor data. Cloud computing, which features scalable and flexible storage and computing services, has been recognized as an ideal candidate that can meet the large data contextual challenges as needed by SSA. Cloud computing consists of physical service providers and middleware virtual machines together with infrastructure, platform, and software as service (IaaS, PaaS, SaaS) models. However, the typical Virtual Machine (VM) abstraction is on a per operating systems basis, which is at too low-level and limits the flexibility of a mission application architecture. In responding to this technical challenge, a novel adaptive process based cloud infrastructure for SSA applications is proposed in this paper. In addition, the details for the design rationale and a prototype is further examined. The SSA Cloud (SSAC) conceptual capability will potentially support space situation monitoring and tracking, object identification, and threat assessment. Lastly, the benefits of a more granular and flexible cloud computing resources allocation are illustrated for data processing and implementation considerations within a representative SSA system environment. We show that the container-based virtualization performs better than hypervisor-based virtualization technology in an SSA scenario.

Explicit Cloud Nucleation from Arbitrary Mixtures of Aerosol Types and Sizes Using an Ultra-Efficient In-Line Aerosol Bin Model in High-Resolution Simulations of Hurricanes

NASA Astrophysics Data System (ADS)

Walko, R. L.; Ashby, T.; Cotton, W. R.

2017-12-01

The fundamental role of atmospheric aerosols in the process of cloud droplet nucleation is well known, and there is ample evidence that the concentration, size, and chemistry of aerosols can strongly influence microphysical, thermodynamic, and ultimately dynamic properties and evolution of clouds and convective systems. With the increasing availability of observation- and model-based environmental representations of different types of anthropogenic and natural aerosols, there is increasing need for models to be able to represent which aerosols nucleate and which do not in supersaturated conditions. However, this is a very complex process that involves competition for water vapor between multiple aerosol species (chemistries) and different aerosol sizes within each species. Attempts have been made to parameterize the nucleation properties of mixtures of different aerosol species, but it is very difficult or impossible to represent all possible mixtures that may occur in practice. As part of a modeling study of the impact of anthropogenic and natural aerosols on hurricanes, we developed an ultra-efficient aerosol bin model to represent nucleation in a high-resolution atmospheric model that explicitly represents cloud- and subcloud-scale vertical motion. The bin model is activated at any time and location in a simulation where supersaturation occurs and is potentially capable of activating new cloud droplets. The bins are populated from the aerosol species that are present at the given time and location and by multiple sizes from each aerosol species according to a characteristic size distribution, and the chemistry of each species is represented by its absorption or adsorption characteristics. The bin model is integrated in time increments that are smaller than that of the atmospheric model in order to temporally resolve the peak supersaturation, which determines the total nucleated number. Even though on the order of 100 bins are typically utilized, this leads only to a 10 or 20% increase in overall computational cost due to the efficiency of the bin model. This method is highly versatile in that it automatically accommodates any possible number and mixture of different aerosol species. Applications of this model to simulations of Typhoon Nuri will be presented.

A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Pergaud, Julien; Masson, Valéry; Malardel, Sylvie; Couvreux, Fleur

2009-07-01

For numerical weather prediction models and models resolving deep convection, shallow convective ascents are subgrid processes that are not parameterized by classical local turbulent schemes. The mass flux formulation of convective mixing is now largely accepted as an efficient approach for parameterizing the contribution of larger plumes in convective dry and cloudy boundary layers. We propose a new formulation of the EDMF scheme (for Eddy DiffusivityMass Flux) based on a single updraft that improves the representation of dry thermals and shallow convective clouds and conserves a correct representation of stratocumulus in mesoscale models. The definition of entrainment and detrainment in the dry part of the updraft is original, and is specified as proportional to the ratio of buoyancy to vertical velocity. In the cloudy part of the updraft, the classical buoyancy sorting approach is chosen. The main closure of the scheme is based on the mass flux near the surface, which is proportional to the sub-cloud layer convective velocity scale w *. The link with the prognostic grid-scale cloud content and cloud cover and the projection on the non- conservative variables is processed by the cloud scheme. The validation of this new formulation using large-eddy simulations focused on showing the robustness of the scheme to represent three different boundary layer regimes. For dry convective cases, this parameterization enables a correct representation of the countergradient zone where the mass flux part represents the top entrainment (IHOP case). It can also handle the diurnal cycle of boundary-layer cumulus clouds (EUROCSARM) and conserve a realistic evolution of stratocumulus (EUROCSFIRE).

In situ observations of snow particle size distributions over a cold frontal rainband within an extratropical cyclone

NASA Astrophysics Data System (ADS)

Yang, Jiefan; Lei, Hengchi

2016-02-01

Cloud microphysical properties of a mixed phase cloud generated by a typical extratropical cyclone in the Tongliao area, Inner Mongolia on 3 May 2014, are analyzed primarily using in situ flight observation data. This study is mainly focused on ice crystal concentration, supercooled cloud water content, and vertical distributions of fit parameters of snow particle size distributions (PSDs). The results showed several discrepancies of microphysical properties obtained during two penetrations. During penetration within precipitating cloud, the maximum ice particle concentration, liquid water content, and ice water content were increased by a factor of 2-3 compared with their counterpart obtained during penetration of a nonprecipitating cloud. The heavy rimed and irregular ice crystals obtained by 2D imagery probe as well as vertical distributions of fitting parameters within precipitating cloud show that the ice particles grow during falling via riming and aggregation process, whereas the lightly rimed and pristine ice particles as well as fitting parameters within non-precipitating cloud indicate the domination of sublimation process. During the two cloud penetrations, the PSDs were generally better represented by gamma distributions than the exponential form in terms of the determining coefficient ( R 2). The correlations between parameters of exponential /gamma form within two penetrations showed no obvious differences compared with previous studies.

Evaluating the feasibility of global climate models to simulate cloud cover effect controlled by Marine Stratocumulus regime transitions

NASA Astrophysics Data System (ADS)

Goren, Tom; Muelmenstaedt, Johannes; Rosenfeld, Daniel; Quaas, Johannes

2017-04-01

Marine stratocumulus clouds (MSC) occur in two main cloud regimes of open and closed cells that differ significantly by their cloud cover. Closed cells gradually get cleansed of high CCN concentrations in a process that involves initiation of drizzle that breaks the full cloud cover into open cells. The drizzle creates downdrafts that organize the convection along converging gust fronts, which in turn produce stronger updrafts that can sustain more cloud water that compensates the depletion of the cloud water by the rain. In addition, having stronger updrafts allow the clouds to grow relatively deep before rain starts to deplete its cloud water. Therefore, lower droplet concentrations and stronger rain would lead to lower cloud fraction, but not necessary also to lower liquid water path (LWP). The fundamental relationships between these key variables derived from global climate model (GCM) simulations are analyzed with respect to observations in order to determine whether the GCM parameterizations can represent well the governing physical mechanisms upon MSC regime transitions. The results are used to evaluate the feasibility of GCM's for estimating aerosol cloud-mediated radiative forcing upon MSC regime transitions, which are responsible for the largest aerosol cloud-mediated radiative forcing.

A microphysical parameterization of aqSOA and sulfate formation in clouds

NASA Astrophysics Data System (ADS)

McVay, Renee; Ervens, Barbara

2017-07-01

Sulfate and secondary organic aerosol (cloud aqSOA) can be chemically formed in cloud water. Model implementation of these processes represents a computational burden due to the large number of microphysical and chemical parameters. Chemical mechanisms have been condensed by reducing the number of chemical parameters. Here an alternative is presented to reduce the number of microphysical parameters (number of cloud droplet size classes). In-cloud mass formation is surface and volume dependent due to surface-limited oxidant uptake and/or size-dependent pH. Box and parcel model simulations show that using the effective cloud droplet diameter (proportional to total volume-to-surface ratio) reproduces sulfate and aqSOA formation rates within ≤30% as compared to full droplet distributions; other single diameters lead to much greater deviations. This single-class approach reduces computing time significantly and can be included in models when total liquid water content and effective diameter are available.

A New WRF-Chem Treatment for Studying Regional Scale Impacts of Cloud-Aerosol Interactions in Parameterized Cumuli

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

Berg, Larry K.; Shrivastava, ManishKumar B.; Easter, Richard C.

A new treatment of cloud-aerosol interactions within parameterized shallow and deep convection has been implemented in WRF-Chem that can be used to better understand the aerosol lifecycle over regional to synoptic scales. The modifications to the model to represent cloud-aerosol interactions include treatment of the cloud dropletnumber mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. Thesechanges have beenmore » implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch cumulus parameterization that has been modified to better represent shallow convective clouds. Preliminary testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS) as well as a high-resolution simulation that does not include parameterized convection. The simulation results are used to investigate the impact of cloud-aerosol interactions on the regional scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +35% for sulfate in non-precipitating conditions due to the sulfate production in the parameterized clouds. The modifications to WRF-Chem version 3.2.1 are found to account for changes in the cloud drop number concentration (CDNC) and changes in the chemical composition of cloud-drop residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to WRF-Chem version 3.5, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

Evaluating the Performance of Single and Double Moment Microphysics Schemes During a Synoptic-Scale Snowfall Event

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.

2011-01-01

Increases in computing resources have allowed for the utilization of high-resolution weather forecast models capable of resolving cloud microphysical and precipitation processes among varying numbers of hydrometeor categories. Several microphysics schemes are currently available within the Weather Research and Forecasting (WRF) model, ranging from single-moment predictions of precipitation content to double-moment predictions that include a prediction of particle number concentrations. Each scheme incorporates several assumptions related to the size distribution, shape, and fall speed relationships of ice crystals in order to simulate cold-cloud processes and resulting precipitation. Field campaign data offer a means of evaluating the assumptions present within each scheme. The Canadian CloudSat/CALIPSO Validation Project (C3VP) represented collaboration among the CloudSat, CALIPSO, and NASA Global Precipitation Measurement mission communities, to observe cold season precipitation processes relevant to forecast model evaluation and the eventual development of satellite retrievals of cloud properties and precipitation rates. During the C3VP campaign, widespread snowfall occurred on 22 January 2007, sampled by aircraft and surface instrumentation that provided particle size distributions, ice water content, and fall speed estimations along with traditional surface measurements of temperature and precipitation. In this study, four single-moment and two double-moment microphysics schemes were utilized to generate hypothetical WRF forecasts of the event, with C3VP data used in evaluation of their varying assumptions. Schemes that incorporate flexibility in size distribution parameters and density assumptions are shown to be preferable to fixed constants, and that a double-moment representation of the snow category may be beneficial when representing the effects of aggregation. These results may guide forecast centers in optimal configurations of their forecast models for winter weather and identify best practices present within these various schemes.

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

Genes2WordCloud: a quick way to identify biological themes from gene lists and free text.

PubMed

Baroukh, Caroline; Jenkins, Sherry L; Dannenfelser, Ruth; Ma'ayan, Avi

2011-10-13

Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications.

Genes2WordCloud: a quick way to identify biological themes from gene lists and free text

PubMed Central

2011-01-01

Background Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Results Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Methods Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Conclusions Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications. PMID:21995939

Aerosol processing in stratiform clouds in ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Neubauer, David; Lohmann, Ulrike; Hoose, Corinna

2013-04-01

Aerosol processing in stratiform clouds by uptake into cloud particles, collision-coalescence, chemical processing inside the cloud particles and release back into the atmosphere has important effects on aerosol concentration, size distribution, chemical composition and mixing state. Aerosol particles can act as cloud condensation nuclei. Cloud droplets can take up further aerosol particles by collisions. Atmospheric gases may also be transferred into the cloud droplets and undergo chemical reactions, e.g. the production of atmospheric sulphate. Aerosol particles are also processed in ice crystals. They may be taken up by homogeneous freezing of cloud droplets below -38° C or by heterogeneous freezing above -38° C. This includes immersion freezing of already immersed aerosol particles in the droplets and contact freezing of particles colliding with a droplet. Many clouds do not form precipitation and also much of the precipitation evaporates before it reaches the ground. The water soluble part of the aerosol particles concentrates in the hydrometeors and together with the insoluble part forms a single, mixed, larger particle, which is released. We have implemented aerosol processing into the current version of the general circulation model ECHAM6 (Stevens et al., 2013) coupled to the aerosol module HAM (Stier et al., 2005). ECHAM6-HAM solves prognostic equations for the cloud droplet number and ice crystal number concentrations. In the standard version of HAM, seven modes are used to describe the total aerosol. The modes are divided into soluble/mixed and insoluble modes and the number concentrations and masses of different chemical components (sulphate, black carbon, organic carbon, sea salt and mineral dust) are prognostic variables. We extended this by an explicit representation of aerosol particles in cloud droplets and ice crystals in stratiform clouds similar to Hoose et al. (2008a,b). Aerosol particles in cloud droplets are represented by 5 tracers for the chemical components as well as 5 tracers for aerosol particles in ice crystals. This allows simulations of aerosol processing in warm, mixed-phase (e.g. through the Bergeron-Findeisen process) and ice clouds. The fixed scavenging ratios used for wet deposition in clouds in standard HAM are replaced by an explicit treatment of collision of cloud droplets/ice crystals with interstitial aerosol particles. Nucleation scavenging of aerosol particles by acting as cloud condensation nuclei or ice nuclei, freezing and evaporation of cloud droplets and melting and sublimation of ice crystals are treated explicitly. In extension to previous studies, aerosol particles from evaporating precipitation are released to modes which correspond to their size. Cloud processing of aerosol particles changes their size distribution and hence influences cloud droplet and ice crystal number concentrations as well as precipitation rate, which in turn affects aerosol concentrations. Results will be presented at the conference. Hoose et al., JGR, 2008a, doi: 10.1029/2007JD009251 Hoose et al., ACP, 2008b, doi: 10.5194/acp-8-6939-2008 Stevens et al., 2013, submitted Stier et al., ACP, 2005, doi: 10.5194/acp-5-1125-2005

Local Interactions of Hydrometeors by Diffusion in Mixed-Phase Clouds

NASA Astrophysics Data System (ADS)

Baumgartner, Manuel; Spichtinger, Peter

2017-04-01

Mixed-phase clouds, containing both ice particles and liquid droplets, are important for the Earth-Atmosphere system. They modulate the radiation budget by a combination of albedo effect and greenhouse effect. In contrast to liquid water clouds, the radiative impact of clouds containing ice particles is still uncertain. Scattering and absorption highly depends in microphysical properties of ice crystals, e.g. size and shape. In addition, most precipitation on Earth forms via the ice phase. Thus, better understanding of ice processes as well as their representation in models is required. A key process for determining shape and size of ice crystals is diffusional growth. Diffusion processes in mixed-phase clouds are highly uncertain; in addition they are usually highly simplified in cloud models, especially in bulk microphysics parameterizations. The direct interaction between cloud droplets and ice particles, due to spatial inhomogeneities, is ignored; the particles can only interact via their environmental conditions. Local effects as supply of supersaturation due to clusters of droplets around ice particles are usually not represented, although they form the physical basis of the Wegener-Bergeron-Findeisen process. We present direct numerical simulations of the interaction of single ice particles and droplets, especially their local competition for the available water vapor. In addition, we show an approach to parameterize local interactions by diffusion. The suggested parameterization uses local steady-state solutions of the diffusion equations for water vapor for an ice particle as well as a droplet. The individual solutions are coupled together to obtain the desired interaction. We show some results of the scheme as implemented in a parcel model.

The beta distribution: A statistical model for world cloud cover

NASA Technical Reports Server (NTRS)

Falls, L. W.

1973-01-01

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

Toward Realistic Simulation of low-Level Clouds Using a Multiscale Modeling Framework With a Third-Order Turbulence Closure in its Cloud-Resolving Model Component

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Cheng, Anning

2010-01-01

This study presents preliminary results from a multiscale modeling framework (MMF) with an advanced third-order turbulence closure in its cloud-resolving model (CRM) component. In the original MMF, the Community Atmosphere Model (CAM3.5) is used as the host general circulation model (GCM), and the System for Atmospheric Modeling with a first-order turbulence closure is used as the CRM for representing cloud processes in each grid box of the GCM. The results of annual and seasonal means and diurnal variability are compared between the modified and original MMFs and the CAM3.5. The global distributions of low-level cloud amounts and precipitation and the amounts of low-level clouds in the subtropics and middle-level clouds in mid-latitude storm track regions in the modified MMF show substantial improvement relative to the original MMF when both are compared to observations. Some improvements can also be seen in the diurnal variability of precipitation.

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

NASA Astrophysics Data System (ADS)

Bony, Sandrine; Stevens, Bjorn; Ament, Felix; Bigorre, Sebastien; Chazette, Patrick; Crewell, Susanne; Delanoë, Julien; Emanuel, Kerry; Farrell, David; Flamant, Cyrille; Gross, Silke; Hirsch, Lutz; Karstensen, Johannes; Mayer, Bernhard; Nuijens, Louise; Ruppert, James H.; Sandu, Irina; Siebesma, Pier; Speich, Sabrina; Szczap, Frédéric; Totems, Julien; Vogel, Raphaela; Wendisch, Manfred; Wirth, Martin

2017-11-01

Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

NASA Astrophysics Data System (ADS)

Bony, Sandrine; Stevens, Bjorn; Ament, Felix; Bigorre, Sebastien; Chazette, Patrick; Crewell, Susanne; Delanoë, Julien; Emanuel, Kerry; Farrell, David; Flamant, Cyrille; Gross, Silke; Hirsch, Lutz; Karstensen, Johannes; Mayer, Bernhard; Nuijens, Louise; Ruppert, James H.; Sandu, Irina; Siebesma, Pier; Speich, Sabrina; Szczap, Frédéric; Totems, Julien; Vogel, Raphaela; Wendisch, Manfred; Wirth, Martin

Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of tradecumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of tradecumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.

Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) Science Plan

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

Wang, Jian; Dong, Xiquan; Wood, Robert

With their extensive coverage, low clouds greatly impact global climate. Presently, low clouds are poorly represented in global climate models (GCMs), and the response of low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The poor representations of low clouds in GCMs are in part due to inadequate observations of their microphysical and macrophysical structures, radiative effects, and the associated aerosol distribution and budget in regions where the aerosol impact is the greatest. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary-layer (MBL) clouds,more » whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. Boundary-layer aerosol in the ENA region is influenced by a variety of sources, leading to strong variations in cloud condensation nuclei (CCN) concentration and aerosol optical properties. Recently a permanent ENA site was established by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility on Graciosa Island in the Azores, providing invaluable information on MBL aerosol and low clouds. At the same time, the vertical structures and horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol, the radiative properties, precipitation efficiency, and lifecycle of MBL clouds, and the cloud response to aerosol perturbations. Much of this data can be obtained only through aircraft-based measurements. In addition, the interconnected aerosol and cloud processes are best investigated by a study involving simultaneous in situ aerosol, cloud, and thermodynamics measurements. Furthermore, in situ measurements are also necessary for validating and improving ground-based retrieval algorithms at the ENA site. This project is motivated by the need for comprehensive in situ characterizations of boundary-layer structure, and associated vertical distributions and horizontal variabilities of low clouds and aerosol over the Azores. ARM Aerial Facility (AAF) Gulfstream-1 (G-1) aircraft will be deployed at the ENA site during two intensive operational periods (IOPs) of early summer (June to July) of 2017 and winter (January to February) of 2018, respectively. Deployments during both seasons allow for examination of key aerosol and cloud processes under a variety of representative meteorological and cloud conditions. The science themes for the deployments include: 1) Budget of MBL CCN and its seasonal variation; 2) Effects of aerosol on cloud and precipitation; 3) Cloud microphysical and macrophysical structures, and entrainment mixing; 4) Advancing retrievals of turbulence, cloud, and drizzle; and 5) Model evaluation and processes studies. A key advantage of the deployments is the strong synergy between the measurements onboard the G-1 and the routine measurements at the ENA site, including state-of-the-art profiling and scanning radars. The 3D cloud structures provided by the scanning radars will put the detailed in situ measurements into mesoscale and cloud lifecycle contexts. On the other hand, high quality in situ measurements will enable validation and improvements of ground-based retrieval algorithms at the ENA site, leading to high-quality and statistically robust data sets from the routine measurements. The deployments, combined with the routine measurements at the ENA site, will have a long lasting impact on the research and modeling of low clouds and aerosols in the remote marine environment.« less

Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications

NASA Astrophysics Data System (ADS)

Cecchini, Micael A.; Machado, Luiz A. T.; Wendisch, Manfred; Costa, Anja; Krämer, Martina; Andreae, Meinrat O.; Afchine, Armin; Albrecht, Rachel I.; Artaxo, Paulo; Borrmann, Stephan; Fütterer, Daniel; Klimach, Thomas; Mahnke, Christoph; Martin, Scot T.; Minikin, Andreas; Molleker, Sergej; Pardo, Lianet H.; Pöhlker, Christopher; Pöhlker, Mira L.; Pöschl, Ulrich; Rosenfeld, Daniel; Weinzierl, Bernadett

2017-12-01

The behavior of tropical clouds remains a major open scientific question, resulting in poor representation by models. One challenge is to realistically reproduce cloud droplet size distributions (DSDs) and their evolution over time and space. Many applications, not limited to models, use the gamma function to represent DSDs. However, even though the statistical characteristics of the gamma parameters have been widely studied, there is almost no study dedicated to understanding the phase space of this function and the associated physics. This phase space can be defined by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and intercomparisons. Here, we introduce the phase space approach and its characteristics, focusing on warm-phase microphysical cloud properties and the transition to the mixed-phase layer. We show that trajectories in this phase space can represent DSD evolution and can be related to growth processes. Condensational and collisional growth may be interpreted as pseudo-forces that induce displacements in opposite directions within the phase space. The actually observed movements in the phase space are a result of the combination of such pseudo-forces. Additionally, aerosol effects can be evaluated given their significant impact on DSDs. The DSDs associated with liquid droplets that favor cloud glaciation can be delimited in the phase space, which can help models to adequately predict the transition to the mixed phase. We also consider possible ways to constrain the DSD in two-moment bulk microphysics schemes, in which the relative dispersion parameter of the DSD can play a significant role. Overall, the gamma phase space approach can be an invaluable tool for studying cloud microphysical evolution and can be readily applied in many scenarios that rely on gamma DSDs.

Exploring clouds, weather, climate, and modeling using bilingual content and activities from the Windows to the Universe program and the Center for Multiscale Modeling of Atmospheric Processes

NASA Astrophysics Data System (ADS)

Foster, S. Q.; Johnson, R. M.; Randall, D.; Denning, S.; Russell, R.; Gardiner, L.; Hatheway, B.; Genyuk, J.; Bergman, J.

2008-12-01

The need for improving the representation of cloud processes in climate models has been one of the most important limitations of the reliability of climate-change simulations. Now in its third year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University is addressing this problem through a revolutionary new approach to representing cloud processes on their native scales, including the cloud-scale interaction processes that are active in cloud systems. CMMAP has set ambitious education and human-resource goals to share basic information about the atmosphere, clouds, weather, climate, and modeling with diverse K-12 and public audiences through its affiliation with the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). W2U web pages are written at three levels in English and Spanish. This information targets learners at all levels, educators, and families who seek to understand and share resources and information about the nature of weather and the climate system, and career role models from related research fields. This resource can also be helpful to educators who are building bridges in the classroom between the sciences, the arts, and literacy. Visitors to the W2U's CMMAP web portal can access a beautiful new clouds image gallery; information about each cloud type and the atmospheric processes that produce them; a Clouds in Art interactive; collections of weather-themed poetry, art, and myths; links to games and puzzles for children; and extensive classroom- ready resources and activities for K-12 teachers. Biographies of CMMAP scientists and graduate students are featured. Basic science concepts important to understanding the atmosphere, such as condensation, atmosphere pressure, lapse rate, and more have been developed, as well as 'microworlds' that enable students to interact with experimental tools while building fundamental knowledge. These resources can be accessed online at no cost by the entire atmospheric science K-12 and informal science education community.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

Ice crystal number concentration measured at mountain-top research stations - What do we measure?

NASA Astrophysics Data System (ADS)

Beck, A.; Henneberger, J.; Fugal, J. P.; David, R.; Larcher, L.; Lohmann, U.

2017-12-01

To assess the impact of surface processes (e.g. blowing snow and hoar frost) on the ice crystal number concentrations (ICNCs) measured at mountain-top research stations, vertical profiles of ICNCs were observed up to a height of 10 m at the Sonnblick Observatory (SBO) in the Hohen Tauern Region, Austria. Independent of the presence of a cloud, the observed ICNCs decrease with height. This suggests a strong impact of surface processes on ICNCs measured at mountain-top research stations. Consequently, the measured ICNCs are not representative of the cloud, which limits the relevance of ground-based measurements for atmospheric studies. When the SBO was cloud free, the observed ICNCs reached several hundreds per liter near the surface and gradually decreased by more than two orders of magnitudes within the observed height interval of 10 m. The observed ice crystals had predominantly irregular habits, which is expected from surface processes. During in-cloud conditions, the ICNCs decreased between a factor of five and ten, if the ICNC at the surface was larger than 100 l-1. For one case study, the ICNC for regular and irregular ice crystals showed a similar relative decrease with height, which is not expected from surface processes. Therefore, we propose two near-surface processes that potentially enrich ICNCs near the surface and explain these findings: Either sedimenting ice crystals are captured in a turbulent layer above the surface or the ICNC is enhanced in a convergence zone, as the cloud is forced over a mountain. These two processes would also have an impact on ICNCs measured at mountain-top stations if the surrounding surface is not snow covered. Thus, ground-based measured ICNCs are uncharacteristic of the cloud properties aloft.

ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

NASA Astrophysics Data System (ADS)

Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

2016-05-01

Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

Hazard mitigation with cloud model based rainfall and convective data

NASA Astrophysics Data System (ADS)

Gernowo, R.; Adi, K.; Yulianto, T.; Seniyatis, S.; Yatunnisa, A. A.

2018-05-01

Heavy rain in Semarang 15 January 2013 causes flood. It is related to dynamic of weather’s parameter, especially with convection process, clouds and rainfall data. In this case, weather condition analysis uses Weather Research and Forecasting (WRF) model used to analyze. Some weather’s parameters show significant result. Their fluctuations prove there is a strong convection that produces convective cloud (Cumulonimbus). Nesting and 2 domains on WRF model show good output to represent weather’s condition commonly. The results of this study different between output cloud cover rate of observation result and output of model around 6-12 hours is because spinning-up of processing. Satellite Images of MTSAT (Multifunctional Transport Satellite) are used as a verification data to prove the result of WRF. White color of satellite image is Coldest Dark Grey (CDG) that indicates there is cloud’s top. This image consolidates that the output of WRF is good enough to analyze Semarang’s condition when the case happened.

MarDRe: efficient MapReduce-based removal of duplicate DNA reads in the cloud.

PubMed

Expósito, Roberto R; Veiga, Jorge; González-Domínguez, Jorge; Touriño, Juan

2017-09-01

This article presents MarDRe, a de novo cloud-ready duplicate and near-duplicate removal tool that can process single- and paired-end reads from FASTQ/FASTA datasets. MarDRe takes advantage of the widely adopted MapReduce programming model to fully exploit Big Data technologies on cloud-based infrastructures. Written in Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for scalable Big Data processing. On a 16-node cluster deployed on the Amazon EC2 cloud platform, MarDRe is up to 8.52 times faster than a representative state-of-the-art tool. Source code in Java and Hadoop as well as a user's guide are freely available under the GNU GPLv3 license at http://mardre.des.udc.es . rreye@udc.es. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Dynamic electronic institutions in agent oriented cloud robotic systems.

PubMed

Nagrath, Vineet; Morel, Olivier; Malik, Aamir; Saad, Naufal; Meriaudeau, Fabrice

2015-01-01

The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.

Global Software Development with Cloud Platforms

NASA Astrophysics Data System (ADS)

Yara, Pavan; Ramachandran, Ramaseshan; Balasubramanian, Gayathri; Muthuswamy, Karthik; Chandrasekar, Divya

Offshore and outsourced distributed software development models and processes are facing challenges, previously unknown, with respect to computing capacity, bandwidth, storage, security, complexity, reliability, and business uncertainty. Clouds promise to address these challenges by adopting recent advances in virtualization, parallel and distributed systems, utility computing, and software services. In this paper, we envision a cloud-based platform that addresses some of these core problems. We outline a generic cloud architecture, its design and our first implementation results for three cloud forms - a compute cloud, a storage cloud and a cloud-based software service- in the context of global distributed software development (GSD). Our ”compute cloud” provides computational services such as continuous code integration and a compile server farm, ”storage cloud” offers storage (block or file-based) services with an on-line virtual storage service, whereas the on-line virtual labs represent a useful cloud service. We note some of the use cases for clouds in GSD, the lessons learned with our prototypes and identify challenges that must be conquered before realizing the full business benefits. We believe that in the future, software practitioners will focus more on these cloud computing platforms and see clouds as a means to supporting a ecosystem of clients, developers and other key stakeholders.

A Novel Tool for Simulating Aerosol-cloud Interactions with a Sectional Model Implemented to a Large-Eddy Simulator

NASA Astrophysics Data System (ADS)

Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Maalick, Z.; Korhonen, H.; Liqing, H.

2015-12-01

A new cloud-resolving model setup for studying aerosol-cloud interactions, with a special emphasis on partitioning and wet deposition of semi-volatile aerosol species, is presented. The model is based on modified versions of two well-established model components: the Large-Eddy Simulator (LES) UCLALES, and the sectional aerosol model SALSA, previously employed in the ECHAM climate model family. Implementation of the UCLALES-SALSA is described in detail. As the basis for this work, SALSA has been extended to include a sectional representation of the size distributions of cloud droplets and precipitation. Microphysical processes operating on clouds and precipitation have also been added. Given our main motivation, the cloud droplet size bins are defined according to the dry particle diameter. The droplet wet diameter is solved dynamically through condensation equations, but represents an average droplet diameter inside each size bin. This approach allows for accurate tracking of the aerosol properties inside clouds, but minimizes the computational cost. Since the actual cloud droplet diameter is not fully resolved inside the size bins, processes such as precipitation formation rely on parameterizations. For realistic growth of drizzle drops to rain, which is critical for the aerosol wet deposition, the precipitation size bins are defined according to the actual drop size. With these additions, the implementation of the SALSA model replaces most of the microphysical and thermodynamical components within the LES. The cloud properties and aerosol-cloud interactions simulated by the model are analysed and evaluated against detailed cloud microphysical boxmodel results and in-situ aerosol-cloud interaction observations from the Puijo measurement station in Kuopio, Finland. The ability of the model to reproduce the impacts of wet deposition on the aerosol population is demonstrated.

SaaS enabled admission control for MCMC simulation in cloud computing infrastructures

NASA Astrophysics Data System (ADS)

Vázquez-Poletti, J. L.; Moreno-Vozmediano, R.; Han, R.; Wang, W.; Llorente, I. M.

2017-02-01

Markov Chain Monte Carlo (MCMC) methods are widely used in the field of simulation and modelling of materials, producing applications that require a great amount of computational resources. Cloud computing represents a seamless source for these resources in the form of HPC. However, resource over-consumption can be an important drawback, specially if the cloud provision process is not appropriately optimized. In the present contribution we propose a two-level solution that, on one hand, takes advantage of approximate computing for reducing the resource demand and on the other, uses admission control policies for guaranteeing an optimal provision to running applications.

Cloud Based Earth Observation Data Exploitation Platforms

NASA Astrophysics Data System (ADS)

Romeo, A.; Pinto, S.; Loekken, S.; Marin, A.

2017-12-01

In the last few years data produced daily by several private and public Earth Observation (EO) satellites reached the order of tens of Terabytes, representing for scientists and commercial application developers both a big opportunity for their exploitation and a challenge for their management. New IT technologies, such as Big Data and cloud computing, enable the creation of web-accessible data exploitation platforms, which offer to scientists and application developers the means to access and use EO data in a quick and cost effective way. RHEA Group is particularly active in this sector, supporting the European Space Agency (ESA) in the Exploitation Platforms (EP) initiative, developing technology to build multi cloud platforms for the processing and analysis of Earth Observation data, and collaborating with larger European initiatives such as the European Plate Observing System (EPOS) and the European Open Science Cloud (EOSC). An EP is a virtual workspace, providing a user community with access to (i) large volume of data, (ii) algorithm development and integration environment, (iii) processing software and services (e.g. toolboxes, visualization routines), (iv) computing resources, (v) collaboration tools (e.g. forums, wiki, etc.). When an EP is dedicated to a specific Theme, it becomes a Thematic Exploitation Platform (TEP). Currently, ESA has seven TEPs in a pre-operational phase dedicated to geo-hazards monitoring and prevention, costal zones, forestry areas, hydrology, polar regions, urban areas and food security. On the technology development side, solutions like the multi cloud EO data processing platform provides the technology to integrate ICT resources and EO data from different vendors in a single platform. In particular it offers (i) Multi-cloud data discovery, (ii) Multi-cloud data management and access and (iii) Multi-cloud application deployment. This platform has been demonstrated with the EGI Federated Cloud, Innovation Platform Testbed Poland and the Amazon Web Services cloud. This work will present an overview of the TEPs and the multi-cloud EO data processing platform, and discuss their main achievements and their impacts in the context of distributed Research Infrastructures such as EPOS and EOSC.

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2015-01-01

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Exploring Properties of HI Clouds in Dwarf Irregular Galaxies

NASA Astrophysics Data System (ADS)

Berger, Clara; Hunter, Deidre Ann

2018-01-01

Dwarf Irregular galaxies form stars and maintain exponential stellar disks at extremely low gas densities. One proposed method of maintaining such regular outer disks is scattering stars off of HI clouds. In order to understand the processes present in dwarf irregular stellar disks, we present a survey of atomic hydrogen clouds in and around a subset of representative galaxies from the LITTLE THINGS survey. We apply a cloud identification program to the 21 cm HI line emission cubes and extract masses, radii, surface densities, and distances from the center of the galaxy in the plane of the galaxy of each cloud. Our data show a wide range of clouds characterized by low surface densities but varied in mass and size. The number of clouds found and the mass of the most massive cloud show no correlation to integrated star forming rates or luminosity in these galaxies. However, they will be used as input for models of stars scattering off of HI clouds to better understand the regular stellar disks in dwarf Irregular galaxies.We acknowledge support from the National Science Foundation grant AST-1461200 to Northern Arizona University for Research Experiences for Undergraduates summer internships.

Cloud Macroscopic Organization: Order Emerging from Randomness

NASA Technical Reports Server (NTRS)

Yuan, Tianle

2011-01-01

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

Cloud microphysical background for the Israel-4 cloud seeding experiment

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Quantifying the impact of anthropogenic pollution on cloud properties derived from ground based remote sensors at the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Maahn, M.; Acquistapace, C.; de Boer, G.; Cox, C.; Feingold, G.; Marke, T.; Williams, C. R.

2017-12-01

When acting as cloud condensation nuclei (CCN) or ice nucleating particles (INPs), aerosols have a strong potential to influence cloud properties. In particular, they can impact the number, size, and phase of cloud particles and potentially cloud lifetime through aerosol indirect and semi-direct effects. In polar regions, these effects are of great importance for the radiation budget due to the shortwave albedo and longwave emissivity of mixed-phase clouds. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program operates two super sites equipped with state of the art ground-based remote sensing instruments in northern Alaska. The sites are both coastal and are highly correlated with respect to large scale synoptic patterns. While the site at Utqiaġvik (formerly known as Barrow) generally represents a relatively pristine Arctic environment lacking significant anthropogenic sources, the site at Oliktok Point, approximately 250 km to the east, is surrounded by the Prudhoe Bay Oil Field, which is the largest oil field in North America. Based on aircraft measurement, the authors recently showed that differences in the properties of liquid clouds properties between the sites can be attributed to local emissions associated with the industrial activities in the Prudhoe Bay region (Maahn et al. 2017, ACPD). However, aircraft measurements do not provide a representative sample of cloud properties due to temporal limitations in the amount of data. In order to investigate how frequently and to what extent liquid cloud properties and processes are modified, we use ground based remote sensing observations such as e.g., cloud radar, Doppler lidar, and microwave radiometer obtained continuously at the two sites. In this way, we are able to quantify inter-site differences with respect to cloud drizzle production, liquid water path, frequency of cloud occurrence, and cloud radiative properties. Turbulence and the coupling of clouds to the boundary layer is investigated in order to infer the potential role of locally emitted aerosols in modulating the observed differences.

Study on the application of mobile internet cloud computing platform

NASA Astrophysics Data System (ADS)

Gong, Songchun; Fu, Songyin; Chen, Zheng

2012-04-01

The innovative development of computer technology promotes the application of the cloud computing platform, which actually is the substitution and exchange of a sort of resource service models and meets the needs of users on the utilization of different resources after changes and adjustments of multiple aspects. "Cloud computing" owns advantages in many aspects which not merely reduce the difficulties to apply the operating system and also make it easy for users to search, acquire and process the resources. In accordance with this point, the author takes the management of digital libraries as the research focus in this paper, and analyzes the key technologies of the mobile internet cloud computing platform in the operation process. The popularization and promotion of computer technology drive people to create the digital library models, and its core idea is to strengthen the optimal management of the library resource information through computers and construct an inquiry and search platform with high performance, allowing the users to access to the necessary information resources at any time. However, the cloud computing is able to promote the computations within the computers to distribute in a large number of distributed computers, and hence implement the connection service of multiple computers. The digital libraries, as a typical representative of the applications of the cloud computing, can be used to carry out an analysis on the key technologies of the cloud computing.

Cloud microphysics modification with an online coupled COSMO-MUSCAT regional model

NASA Astrophysics Data System (ADS)

Sudhakar, D.; Quaas, J.; Wolke, R.; Stoll, J.; Muehlbauer, A. D.; Tegen, I.

2015-12-01

Abstract: The quantification of clouds, aerosols, and aerosol-cloud interactions in models, continues to be a challenge (IPCC, 2013). In this scenario two-moment bulk microphysical scheme is used to understand the aerosol-cloud interactions in the regional model COSMO (Consortium for Small Scale Modeling). The two-moment scheme in COSMO has been especially designed to represent aerosol effects on the microphysics of mixed-phase clouds (Seifert et al., 2006). To improve the model predictability, the radiation scheme has been coupled with two-moment microphysical scheme. Further, the cloud microphysics parameterization has been modified via coupling COSMO with MUSCAT (MultiScale Chemistry Aerosol Transport model, Wolke et al., 2004). In this study, we will be discussing the initial result from the online-coupled COSMO-MUSCAT model system with modified two-moment parameterization scheme along with COSP (CFMIP Observational Simulator Package) satellite simulator. This online coupled model system aims to improve the sub-grid scale process in the regional weather prediction scenario. The constant aerosol concentration used in the Seifert and Beheng, (2006) parameterizations in COSMO model has been replaced by aerosol concentration derived from MUSCAT model. The cloud microphysical process from the modified two-moment scheme is compared with stand-alone COSMO model. To validate the robustness of the model simulation, the coupled model system is integrated with COSP satellite simulator (Muhlbauer et al., 2012). Further, the simulations are compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and ISCCP (International Satellite Cloud Climatology Project) satellite products.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Ship Tracks in the Sky

NASA Technical Reports Server (NTRS)

2002-01-01

Because clouds represent an area of great uncertainty in studies of global climate, scientists are interested in better understanding the processes by which clouds form and change over time. In recent years, scientists have turned their attention to the ways in which human-produced aerosol pollution modifies clouds. One area that has drawn scientists' attention is 'ship tracks,' or clouds that form from the sulfate aerosols released by large ships. Although ships are not significant sources of pollution themselves, they do release enough sulfur dioxide in the exhaust from their smokestacks to modify overlying clouds. Specifically, the aerosol particles formed by the ship exhaust in the atmosphere cause the clouds to be more reflective, carry more water, and possibly inhibit them from precipitating. This is one example of how humans have been creating and modifying clouds for generations through the burning of fossil fuels. This image was acquired over the northern Pacific Ocean by the Moderate-resolution Imaging Spectroradiometer (MODIS), flying aboard NASA's Terra satellite, on April 29, 2002. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur

2012-01-01

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

A Cloud Hydrology and Albedo Synthesis Mission (CHASM)

NASA Technical Reports Server (NTRS)

Davies, Roger

2004-01-01

This slide presentation reviews the Cloud Hydrology and Albedo Synthesis Mission (CHASM). The interaction of clouds with radiation and the hydrological cycle represents a huge uncertainty in our understanding of climate science and the modeling of climate system feedbacks. Despite the recognized need for a unified treatment of cloud processes, the present global average values of remotely sensed cloud liquid water and theoretically accepted values used for cloud physics and precipitation modeling differ by an order of magnitude. This is due in part to sampling and saturation effects, as well as to threedimensional cloud structure effects. In recent work with the Multiangle Imaging SpectroRadiometer (MISR) on Terra, we have gained new insights as to how the remote sensing approach could be significantly improved using a new instrument that combines passive optical (visible and near infrared) and microwave measurements, both as pushbroom scanners with multiple viewing angles, to the degree that measurements of liquid water path over deep convective clouds over land also become possible. This instrument would also have the ability of measuring height-resolved cloud-tracked winds using a hyper stereo retrieval technique. Deployment into a precessing low earth orbit would be optimal for measuring diurnal cloud activity. We have explored an instrument design concept for this that looks promising if we can establish partnerships that provide launch and bus capabilities.

Prototyping manufacturing in the cloud

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2017-08-01

This paper attempts a theoretical approach to cloud systems with impacts on production systems. I call systems as cloud computing because form a relatively new concept in the field of informatics, representing an overall distributed computing services, applications, access to information and data storage without the user to know the physical location and configuration of systems. The advantages of this approach are especially computing speed and storage capacity without investment in additional configurations, synchronizing user data, data processing using web applications. The disadvantage is that it wants to identify a solution for data security, leading to mistrust users. The case study is applied to a module of the system of production, because the system is complex.

Evolution of bubble clouds induced by pulsed cavitational ultrasound therapy - histotripsy.

PubMed

Xu, Zhen; Raghavan, M; Hall, T L; Mycek, M-A; Fowlkes, J B

2008-05-01

Mechanical tissue fractionation can be achieved using successive, high-intensity ultrasound pulses in a process termed histotripsy. Histotripsy has many potential clinical applications where noninvasive tissue removal is desired. The primary mechanism for histotripsy is believed to be cavitation. Using fast-gated imaging, this paper studies the evolution of a cavitating bubble cloud induced by a histotripsy pulse (10 and 14 cycles) at peak negative pressures exceeding 21MPa. Bubble clouds are generated inside a gelatin phantom and at a tissue-water interface, representing two situations encountered clinically. In both environments, the imaging results show that the bubble clouds share the same evolutionary trend. The bubble cloud and individual bubbles in the cloud were generated by the first cycle of the pulse, grew with each cycle during the pulse, and continued to grow and collapsed several hundred microseconds after the pulse. For example, the bubbles started under 10 microm, grew to 50 microm during the pulse, and continued to grow 100 microm after the pulse. The results also suggest that the bubble clouds generated in the two environments differ in growth and collapse duration, void fraction, shape, and size. This study furthers our understanding of the dynamics of bubble clouds induced by histotripsy.

The effect of clouds on photolysis rates and ozone formation in the unpolluted troposphere

NASA Technical Reports Server (NTRS)

Thompson, A. M.

1984-01-01

The photochemistry of the lower atmosphere is sensitive to short- and long-term meteorological effects; accurate modeling therefore requires photolysis rates for trace gases which reflect this variability. As an example, the influence of clouds on the production of tropospheric ozone has been investigated, using a modification of Luther's two-stream radiation scheme to calculate cloud-perturbed photolysis rates in a one-dimensional photochemical transport model. In the unpolluted troposphere, where stratospheric inputs of odd nitrogen appear to represent the photochemical source of O3, strong cloud reflectance increases the concentration of NO in the upper troposphere, leading to greatly enhanced rates of ozone formation. Although the rate of these processes is too slow to verify by observation, the calculation is useful in distinguishing some features of the chemistry of regions of differing mean cloudiness.

GCSS Idealized Cirrus Model Comparison Project

NASA Technical Reports Server (NTRS)

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

Evapotranspiration and cloud variability at regional sub-grid scales

NASA Astrophysics Data System (ADS)

Vila-Guerau de Arellano, Jordi; Sikma, Martin; Pedruzo-Bagazgoitia, Xabier; van Heerwaarden, Chiel; Hartogensis, Oscar; Ouwersloot, Huug

2017-04-01

In regional and global models uncertainties arise due to our incomplete understanding of the coupling between biochemical and physical processes. Representing their impact depends on our ability to calculate these processes using physically sound parameterizations, since they are unresolved at scales smaller than the grid size. More specifically over land, the coupling between evapotranspiration, turbulent transport of heat and moisture, and clouds lacks a combined representation to take these sub-grid scales interactions into account. Our approach is based on understanding how radiation, surface exchange, turbulent transport and moist convection are interacting from the leaf- to the cloud scale. We therefore place special emphasis on plant stomatal aperture as the main regulator of CO2-assimilation and water transpiration, a key source of moisture source to the atmosphere. Plant functionality is critically modulated by interactions with atmospheric conditions occurring at very short spatiotemporal scales such as cloud radiation perturbations or water vapour turbulent fluctuations. By explicitly resolving these processes, the LES (large-eddy simulation) technique is enabling us to characterize and better understand the interactions between canopies and the local atmosphere. This includes the adaption time of vegetation to rapid changes in atmospheric conditions driven by turbulence or the presence of cumulus clouds. Our LES experiments are based on explicitly coupling the diurnal atmospheric dynamics to a plant physiology model. Our general hypothesis is that different partitioning of direct and diffuse radiation leads to different responses of the vegetation. As a result there are changes in the water use efficiencies and shifts in the partitioning of sensible and latent heat fluxes under the presence of clouds. Our presentation is as follows. First, we discuss the ability of LES to reproduce the surface energy balance including photosynthesis and CO2 soil respiration coupled to the dynamics of a convective boundary layer. LES results are compared with a complete set of surface and upper-air meteorological and carbon-dioxide observations gathered during a representative day at the 213-meter meteorological tall tower at Cabauw. Second, we perform systematic numerical experiments under a wide range of background wind conditions and stomatal aperture response time. Our analysis unravel how thin clouds, characterized by lower values of the cloud optical depth, have a different impact on evapotranspiration compared to thick clouds due to differences in the partitioning between direct and diffuse radiation at canopy level. Related to this detailed simulation, we discuss how new instrumental techniques, e.g. scintillometery, enable us to obtain new observational insight of the coupling between clouds and vegetation. We will close the presentation with open questions regarding the need to include parameterizations for these interactions at short spatiotemporal scales in regional or climate models.

Electromagnetic Methods of Lightning Detection

NASA Astrophysics Data System (ADS)

Rakov, V. A.

2013-11-01

Both cloud-to-ground and cloud lightning discharges involve a number of processes that produce electromagnetic field signatures in different regions of the spectrum. Salient characteristics of measured wideband electric and magnetic fields generated by various lightning processes at distances ranging from tens to a few hundreds of kilometers (when at least the initial part of the signal is essentially radiation while being not influenced by ionospheric reflections) are reviewed. An overview of the various lightning locating techniques, including magnetic direction finding, time-of-arrival technique, and interferometry, is given. Lightning location on global scale, when radio-frequency electromagnetic signals are dominated by ionospheric reflections, is also considered. Lightning locating system performance characteristics, including flash and stroke detection efficiencies, percentage of misclassified events, location accuracy, and peak current estimation errors, are discussed. Both cloud and cloud-to-ground flashes are considered. Representative examples of modern lightning locating systems are reviewed. Besides general characterization of each system, the available information on its performance characteristics is given with emphasis on those based on formal ground-truth studies published in the peer-reviewed literature.

Estimating Cloud Cover

ERIC Educational Resources Information Center

Moseley, Christine

2007-01-01

The purpose of this activity was to help students understand the percentage of cloud cover and make more accurate cloud cover observations. Students estimated the percentage of cloud cover represented by simulated clouds and assigned a cloud cover classification to those simulations. (Contains 2 notes and 3 tables.)

ISOPRENE FORMS SECONDARY ORGANIC AEROSOL THROUGH CLOUD PROCESSING: MODEL SIMULATIONS (R831073)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Evaluation of Cirrus Cloud Simulations Using ARM Data - Development of a Case Study Data Set

NASA Technical Reports Server (NTRS)

O'C.Starr, David; Demoz, Belay; Lare, Andrew; Poellot, Michael; Sassen, Kenneth; Heymsfield, Andrew; Brown, Philip; Mace, Jay; Einaudi, Franco (Technical Monitor)

2001-01-01

Cloud-resolving models (CRMs) provide an effective linkage in terms of parameters and scales between observations and the parametric treatments of clouds in global climate models (GCMs). They also represent the best understanding of the physical processes acting to determine cloud system lifecycle. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. This project will compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. The environmental data (input) will be described as well as the wealth of validating cloud observations. We plan to also show results of preliminary simulations. The science questions to be addressed derive significantly from results of the GCSS WG2 cloud model comparison projects, which will be briefly summarized.

Observing ice particle growth along fall streaks in mixed-phase clouds using spectral polarimetric radar data

NASA Astrophysics Data System (ADS)

Pfitzenmaier, Lukas; Unal, Christine M. H.; Dufournet, Yann; Russchenberg, Herman W. J.

2018-06-01

The growth of ice crystals in presence of supercooled liquid droplets represents the most important process for precipitation formation in the mid-latitudes. However, such mixed-phase interaction processes remain relatively unknown, as capturing the complexity in cloud dynamics and microphysical variabilities turns to be a real observational challenge. Ground-based radar systems equipped with fully polarimetric and Doppler capabilities in high temporal and spatial resolutions such as the S-band transportable atmospheric radar (TARA) are best suited to observe mixed-phase growth processes. In this paper, measurements are taken with the TARA radar during the ACCEPT campaign (analysis of the composition of clouds with extended polarization techniques). Besides the common radar observables, the 3-D wind field is also retrieved due to TARA unique three beam configuration. The novelty of this paper is to combine all these observations with a particle evolution detection algorithm based on a new fall streak retrieval technique in order to study ice particle growth within complex precipitating mixed-phased cloud systems. In the presented cases, three different growth processes of ice crystals, plate-like crystals, and needles are detected and related to the presence of supercooled liquid water. Moreover, TARA observed signatures are assessed with co-located measurements obtained from a cloud radar and radiosondes. This paper shows that it is possible to observe ice particle growth processes within complex systems taking advantage of adequate technology and state of the art retrieval algorithms. A significant improvement is made towards a conclusive interpretation of ice particle growth processes and their contribution to rain production using fall streak rearranged radar data.

Modelling ice microphysics of mixed-phase clouds

NASA Astrophysics Data System (ADS)

Ahola, J.; Raatikainen, T.; Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Korhonen, H.

2017-12-01

The low-level Arctic mixed-phase clouds have a significant role for the Arctic climate due to their ability to absorb and reflect radiation. Since the climate change is amplified in polar areas, it is vital to apprehend the mixed-phase cloud processes. From a modelling point of view, this requires a high spatiotemporal resolution to capture turbulence and the relevant microphysical processes, which has shown to be difficult.In order to solve this problem about modelling mixed-phase clouds, a new ice microphysics description has been developed. The recently published large-eddy simulation cloud model UCLALES-SALSA offers a good base for a feasible solution (Tonttila et al., Geosci. Mod. Dev., 10:169-188, 2017). The model includes aerosol-cloud interactions described with a sectional SALSA module (Kokkola et al., Atmos. Chem. Phys., 8, 2469-2483, 2008), which represents a good compromise between detail and computational expense.Newly, the SALSA module has been upgraded to include also ice microphysics. The dynamical part of the model is based on well-known UCLA-LES model (Stevens et al., J. Atmos. Sci., 56, 3963-3984, 1999) which can be used to study cloud dynamics on a fine grid.The microphysical description of ice is sectional and the included processes consist of formation, growth and removal of ice and snow particles. Ice cloud particles are formed by parameterized homo- or heterogeneous nucleation. The growth mechanisms of ice particles and snow include coagulation and condensation of water vapor. Autoconversion from cloud ice particles to snow is parameterized. The removal of ice particles and snow happens by sedimentation and melting.The implementation of ice microphysics is tested by initializing the cloud simulation with atmospheric observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC). The results are compared to the model results shown in the paper of Ovchinnikov et al. (J. Adv. Model. Earth Syst., 6, 223-248, 2014) and they show a good match. One of the advantages of UCLALES-SALSA is that it can be used to quantify the effect of aerosol scavenging on cloud properties in a precise way.

An A-Train Climatology of Extratropical Cyclone Clouds

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Energy-based and process-based constraints on aerosol-climate interaction

NASA Astrophysics Data System (ADS)

Suzuki, K.; Sato, Y.; Takemura, T.; Michibata, T.; Goto, D.; Oikawa, E.

2017-12-01

Recent advance in both satellite observations and global modeling provides us with a novel opportunity to investigate the long-standing aerosol-climate interaction issue at a fundamental process level, particularly with a combined use of them. In this presentation, we will highlight our recent progress in understanding the aerosol-cloud-precipitation interaction and its implication for global climate with a synergistic use of a state-of-the-art global climate model (MIROC), a global cloud-resolving model (NICAM) and recent satellite observations (A-Train). In particular, we explore two different aspects of the aerosol-climate interaction issue, i.e. (i) the global energy balance perspective with its modulation due to aerosols and (ii) the process-level characteristics of the aerosol-induced perturbations to cloud and precipitation. For the former, climate model simulations are used to quantify how components of global energy budget are modulated by the aerosol forcing. The moist processes are shown to be a critical pathway that links the forcing efficacy and the hydrologic sensitivity arising from aerosol perturbations. Effects of scattering (e.g. sulfate) and absorbing (e.g. black carbon) aerosols are compared in this context to highlight their distinctively different impacts on climate and hydrologic cycle. The aerosol-induced modulation of moist processes is also investigated in the context of the second aspect above to facilitate recent arguments on possible overestimates of the aerosol-cloud interaction in climate models. Our recent simulations with NICAM are shown to highlight how diverse responses of cloud to aerosol perturbation, which have been failed to represent in traditional climate models, are reproduced by the high-resolution global model with sophisticated cloud microphysics. We will discuss implications of these findings for a linkage between the two aspects above to aid advance process-based understandings of the aerosol-climate interaction and also to mitigate a "dichotomy" recently found by the authors between the two aspects in the context of the climate projection.

Water Ice Clouds as Seen from the Mars Exploration Rovers

NASA Astrophysics Data System (ADS)

Wolff, M. J.; Clancy, R. T.; Banfield, D.; Cuozzo, K.

2005-12-01

Water ice clouds that bear a striking resemblance to terrestrial cirrus (e.g., "Mare's tails") have been observed by the Panoramic Camera (Pancam), the Navigation Camera (Navcam), the Hazard Camera (Hazcam), and the Minature Thermal Emission Spectrometer (Mini-TES) on board the Mars Exploration Rovers (MER). Such phenomena represent an opportunity to characterize local and regional scale meteorology as well as our understanding of the processes involved. However, a necessary first-step is to adequately describe some basic properties of the detected clouds: 1) when are the clouds present (i.e., local time, season, etc.)? 2) where are the clouds present? That is to say, what is the relative frequency between the two rover sites as well as the connection to detections from orbiting spacecraft. 3) what are the observed morphologies? 4) what are the projected velocities (i.e., wind speeds and directions) associated with the clouds? 5) what is the abundance of water ice nuclei (i.e., optical depth)? Our talk will summarize our progress in answering the above questions, as well as provide initial results in connecting the observations to more global behavior in the Martian climate.

Parameterization of cloud glaciation by atmospheric dust

NASA Astrophysics Data System (ADS)

Nickovic, Slobodan; Cvetkovic, Bojan; Madonna, Fabio; Pejanovic, Goran; Petkovic, Slavko

2016-04-01

The exponential growth of research interest on ice nucleation (IN) is motivated, inter alias, by needs to improve generally unsatisfactory representation of cold cloud formation in atmospheric models, and therefore to increase the accuracy of weather and climate predictions, including better forecasting of precipitation. Research shows that mineral dust significantly contributes to cloud ice nucleation. Samples of residual particles in cloud ice crystals collected by aircraft measurements performed in the upper tropopause of regions distant from desert sources indicate that dust particles dominate over other known ice nuclei such as soot and biological particles. In the nucleation process, dust chemical aging had minor effects. The observational evidence on IN processes has substantially improved over the last decade and clearly shows that there is a significant correlation between IN concentrations and the concentrations of coarser aerosol at a given temperature and moisture. Most recently, due to recognition of the dominant role of dust as ice nuclei, parameterizations for immersion and deposition icing specifically due to dust have been developed. Based on these achievements, we have developed a real-time forecasting coupled atmosphere-dust modelling system capable to operationally predict occurrence of cold clouds generated by dust. We have been thoroughly validated model simulations against available remote sensing observations. We have used the CNR-IMAA Potenza lidar and cloud radar observations to explore the model capability to represent vertical features of the cloud and aerosol vertical profiles. We also utilized the MSG-SEVIRI and MODIS satellite data to examine the accuracy of the simulated horizontal distribution of cold clouds. Based on the obtained encouraging verification scores, operational experimental prediction of ice clouds nucleated by dust has been introduced in the Serbian Hydrometeorological Service as a public available product.

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.

Diurnal cycle of precipitation at Dakar in the model LMDZ

NASA Astrophysics Data System (ADS)

Sane, Y.; Bonazzola, M.; Hourdin, F.; Diongue-Niang, A.

2009-04-01

Most diurnal cycles of precipitation are not well represented in general circulation models (GCMs). It is a concern for climate modeling because of the key role of clouds in the radiative and water budgets. The diurnal phasing of deep convection is a challenge, the pact of deep convection being generally simulated too early in the day (Guichard et al., 2004). Thus a "thermal plume model" - a mass flux scheme combined with a classical diffusive approach - originally developed to represent turbulent transport in the dry convective boundary layer, is extented to the representation of cloud processes. The modified parametrization was validated in a 1D configuration against results of large eddy simulations (Rio, 2008). It is here validated in a 3D configuration against in situ precipitation measurements of the AMMA campaign. A data analysis of the diurnal cycle of precipitation as measured by the pluviometers net in the Dakar area is performed. The improvement of the diurnal cyle of convection in the GCM is demonstrated, and the involved processes are analysed.

Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model

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

Wall, Casey J.; Hartmann, Dennis L.; Ma, Po-Lun

Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the middle-troposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm- and cold-sector of cyclones. The observed relationships between clouds andmore » meteorology are compared to those in the Community Atmosphere Model version 5 (CAM5) using satellite simulators. Low-clouds simulated by CAM5 are too few, too bright, and contain too much ice, and low-clouds located in the cold-sector of cyclones are too sensitive to variations in the meteorology. The latter two biases are dramatically reduced when CAM5 is coupled with an updated boundary layer parameterization know as Cloud Layers Unified by Binormals (CLUBB). More generally, this study demonstrates that examining the instantaneous timescale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.« less

Street curb recognition in 3d point cloud data using morphological operations

NASA Astrophysics Data System (ADS)

Rodríguez-Cuenca, Borja; Concepción Alonso-Rodríguez, María; García-Cortés, Silverio; Ordóñez, Celestino

2015-04-01

Accurate and automatic detection of cartographic-entities saves a great deal of time and money when creating and updating cartographic databases. The current trend in remote sensing feature extraction is to develop methods that are as automatic as possible. The aim is to develop algorithms that can obtain accurate results with the least possible human intervention in the process. Non-manual curb detection is an important issue in road maintenance, 3D urban modeling, and autonomous navigation fields. This paper is focused on the semi-automatic recognition of curbs and street boundaries using a 3D point cloud registered by a mobile laser scanner (MLS) system. This work is divided into four steps. First, a coordinate system transformation is carried out, moving from a global coordinate system to a local one. After that and in order to simplify the calculations involved in the procedure, a rasterization based on the projection of the measured point cloud on the XY plane was carried out, passing from the 3D original data to a 2D image. To determine the location of curbs in the image, different image processing techniques such as thresholding and morphological operations were applied. Finally, the upper and lower edges of curbs are detected by an unsupervised classification algorithm on the curvature and roughness of the points that represent curbs. The proposed method is valid in both straight and curved road sections and applicable both to laser scanner and stereo vision 3D data due to the independence of its scanning geometry. This method has been successfully tested with two datasets measured by different sensors. The first dataset corresponds to a point cloud measured by a TOPCON sensor in the Spanish town of Cudillero. That point cloud comprises more than 6,000,000 points and covers a 400-meter street. The second dataset corresponds to a point cloud measured by a RIEGL sensor in the Austrian town of Horn. That point cloud comprises 8,000,000 points and represents a 160-meter street. The proposed method provides success rates in curb recognition of over 85% in both datasets.

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

NASA Astrophysics Data System (ADS)

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

2007-07-01

The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and -35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to -1.9 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to -0.7 W m-2. The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Global aerosol effects on convective clouds

NASA Astrophysics Data System (ADS)

Wagner, Till; Stier, Philip

2013-04-01

Atmospheric aerosols affect cloud properties, and thereby the radiation balance of the planet and the water cycle. The influence of aerosols on clouds is dominated by increase of cloud droplet and ice crystal numbers (CDNC/ICNC) due to enhanced aerosols acting as cloud condensation and ice nuclei. In deep convective clouds this increase in CDNC/ICNC is hypothesised to increase precipitation because of cloud invigoration through enhanced freezing and associated increased latent heat release caused by delayed warm rain formation. Satellite studies robustly show an increase of cloud top height (CTH) and precipitation with increasing aerosol optical depth (AOD, as proxy for aerosol amount). To represent aerosol effects and study their influence on convective clouds in the global climate aerosol model ECHAM-HAM, we substitute the standard convection parameterisation, which uses one mean convective cloud for each grid column, with the convective cloud field model (CCFM), which simulates a spectrum of convective clouds, each with distinct values of radius, mixing ratios, vertical velocity, height and en/detrainment. Aerosol activation and droplet nucleation in convective updrafts at cloud base is the primary driver for microphysical aerosol effects. To produce realistic estimates for vertical velocity at cloud base we use an entraining dry parcel sub cloud model which is triggered by perturbations of sensible and latent heat at the surface. Aerosol activation at cloud base is modelled with a mechanistic, Köhler theory based, scheme, which couples the aerosols to the convective microphysics. Comparison of relationships between CTH and AOD, and precipitation and AOD produced by this novel model and satellite based estimates show general agreement. Through model experiments and analysis of the model cloud processes we are able to investigate the main drivers for the relationship between CTH / precipitation and AOD.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

Kunishima, Y.; Onishi, R.

2017-12-01

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

ARC-1986-AC86-7008

NASA Image and Video Library

1986-01-14

Range : 12.9 million miles (8.0 million miles) P-29468C This false color Voyager photograph of Uranus shows a discrete cloud seen as a bright streak near the planets limb. The cloud visible here is the most prominent feature seen in a series of Voyager images designed to track atmospheric motions. The occasional donut shaped features, including one at the bottom, are shadows cast by dust on the camera optics. The picture is a highly processed composite of three images. The processing necessary to bring out the faint features on the planet also brings out these camera blemishes. The three seperate images used where shot through violet, blue, and orange filters. Each color image showd the cloud to a different degree; because they were not exposed at the same time , the images were processed to provide a good spatial match. In a true color image, the cloud would be barely discernable; the false color helps to bring out additional details. The different colors imply variations in vertical structure, but as of yet it is not possible to be specific about such differences. One possiblity is that the uranian atmosphere may contain smog like constituents, in which case some color differences may represent differences in how these molecules are distributed.

EDITORIAL: Focus on Cloud Physics FOCUS ON CLOUD PHYSICS

NASA Astrophysics Data System (ADS)

Falkovich, Gregory; Malinowski, Szymon P.

2008-07-01

Cloud physics has for a long time been an important segment of atmospheric science. It is common knowledge that clouds are crucial for our understanding of weather and climate. Clouds are also interesting by themselves (not to mention that they are beautiful). Complexity is hidden behind the common picture of these beautiful and interesting objects. The typical school textbook definition that a cloud is 'a set of droplets or particles suspended in the atmosphere' is not adequate. Clouds are complicated phenomena in which dynamics, turbulence, microphysics, thermodynamics and radiative transfer interact on a wide range of scales, from sub-micron to kilometres. Some of these interactions are subtle and others are more straightforward. Large and small-scale motions lead to activation of cloud condensation nuclei, condensational growth and collisions; small changes in composition and concentration of atmospheric aerosol lead to significant differences in radiative properties of the clouds and influence rainfall formation. It is justified to look at a cloud as a composite, nonlinear system which involves many interactions and feedback. This system is actively linked into a web of atmospheric, oceanic and even cosmic interactions. Due to the complexity of the cloud system, present-day descriptions of clouds suffer from simplifications, inadequate parameterizations, and omissions. Sometimes the most fundamental physics hidden behind these simplifications and parameterizations is not known, and a wide scope of view can sometimes prevent a 'microscopic', deep insight into the detail. Only the expertise offered by scientists focused on particular elementary processes involved in this complicated pattern of interactions allows us to shape elements of the puzzle from which a general picture of clouds can be created. To be useful, every element of the puzzle must be shaped precisely. This often creates problems in communication between the sciences responsible for shaping elements of the puzzle, and those which combine them. Scales, assumptions and the conditions used in order to describe a particular single process of interest must be consistent with the conditions in clouds. The papers in this focus issue of New Journal of Physics collectively demonstrate (i) the variation in scientific approaches towards investigating cloud processes, (ii) the various stages of shaping elements of the puzzle, and (iii) some attempts to put the pieces together. These papers present just a small subset of loosely arranged elements in an initial stage of puzzle creation. Addressed by this issue is one of the important problems in our understanding of cloud processes—the interaction between cloud particles and turbulence. There is currently a gap between the cloud physics community and scientists working in wind tunnels, on turbulence theory and particle interactions. This collection is intended to narrow this gap by bringing together work by theoreticians, modelers, laboratory experimentalists and those who measure and observe actual processes in clouds. It forms a collage of contributions showing various approaches to cloud processes including: • theoretical works with possible applications to clouds (Bistagnino and Boffetta, Gustavsson et al), • an attempt to construct a phenomenological description of clouds and rain (Lovejoy and Schertzer), • simplified models designed to parameterize turbulence micro- and macro-effects (Celani et al, Derevyanko et al), • focused theoretical research aimed at particular cloud processes (Ayala et al, parts I and II, Wang et al), • laboratory and modeling studies of complex cloud processes (Malinowski et al). This collage is far from being complete but, hopefully, should give the reader a representative impression of the current state of knowledge in the field. We hope it will be useful to all scientists whose work is inspired by cloud processes. Focus on Cloud Physics Contents The equivalent size of cloud condensation nuclei Antonio Celani, Andrea Mazzino and Marco Tizzi Laboratory and modeling studies of cloud-clear air interfacial mixing: anisotropy of small-scale turbulence due to evaporative cooling Szymon P Malinowski, Miroslaw Andrejczuk, Wojciech W Grabowski, Piotr Korczyk, Tomasz A Kowalewski and Piotr K Smolarkiewicz Evolution of non-uniformly seeded warm clouds in idealized turbulent conditions Stanislav Derevyanko, Gregory Falkovich and Sergei Turitsyn Lagrangian statistics in two-dimensional free turbulent convection A Bistagnino and G Boffetta Turbulence, raindrops and the l1/2 number density law S Lovejoy and D Schertzer Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization Orlando Ayala, Bogdan Rosa and Lian-Ping Wang Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 1. Results from direct numerical simulation Orlando Ayala, Bogdan Rosa, Lian-Ping Wang and Wojciech W Grabowski Collisions of particles advected in random flows K Gustavsson, B Mehlig and M Wilkinson Turbulent collision efficiency of heavy particles relevant to cloud droplets Lian-Ping Wang, Orlando Ayala, Bogdan Rosa and Wojciech W Grabowski

Introducing Convective Cloud Microphysics to a Deep Convection Parameterization Facilitating Aerosol Indirect Effects

NASA Astrophysics Data System (ADS)

Alapaty, K.; Zhang, G. J.; Song, X.; Kain, J. S.; Herwehe, J. A.

2012-12-01

Short lived pollutants such as aerosols play an important role in modulating not only the radiative balance but also cloud microphysical properties and precipitation rates. In the past, to understand the interactions of aerosols with clouds, several cloud-resolving modeling studies were conducted. These studies indicated that in the presence of anthropogenic aerosols, single-phase deep convection precipitation is reduced or suppressed. On the other hand, anthropogenic aerosol pollution led to enhanced precipitation for mixed-phase deep convective clouds. To date, there have not been many efforts to incorporate such aerosol indirect effects (AIE) in mesoscale models or global models that use parameterization schemes for deep convection. Thus, the objective of this work is to implement a diagnostic cloud microphysical scheme directly into a deep convection parameterization facilitating aerosol indirect effects in the WRF-CMAQ integrated modeling systems. Major research issues addressed in this study are: What is the sensitivity of a deep convection scheme to cloud microphysical processes represented by a bulk double-moment scheme? How close are the simulated cloud water paths as compared to observations? Does increased aerosol pollution lead to increased precipitation for mixed-phase clouds? These research questions are addressed by performing several WRF simulations using the Kain-Fritsch convection parameterization and a diagnostic cloud microphysical scheme. In the first set of simulations (control simulations) the WRF model is used to simulate two scenarios of deep convection over the continental U.S. during two summer periods at 36 km grid resolution. In the second set, these simulations are repeated after incorporating a diagnostic cloud microphysical scheme to study the impacts of inclusion of cloud microphysical processes. Finally, in the third set, aerosol concentrations simulated by the CMAQ modeling system are supplied to the embedded cloud microphysical scheme to study impacts of aerosol concentrations on precipitation and radiation fields. Observations available from the ARM microbase data, the SURFRAD network, GOES imagery, and other reanalysis and measurements will be used to analyze the impacts of a cloud microphysical scheme and aerosol concentrations on parameterized convection.

Evaluation of ERA-interim and MERRA Cloudiness in the Southern Oceans

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.

2014-01-01

The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

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

Zheng, Xue; Klein, S. A.; Ma, H. -Y.

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

DOE PAGES

Zheng, Xue; Klein, S. A.; Ma, H. -Y.; ...

2016-07-19

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less

Effects of Wildfire Pollution on the Microphysical and Electrical Properties of Pyrocumulus

NASA Astrophysics Data System (ADS)

Duff, R.; Grant, L. D.; van den Heever, S. C.

2014-12-01

Pyrocumulus clouds form over wildfires when hot, smoke-filled air rises, cools and condenses. These clouds have higher cloud condensation nuclei (CCN) concentrations, which affect their microphysical and electrical properties. It is important to better understand pyrocumulus cloud microphysical characteristics and lightning formation, which have implications for the prediction of wildfire growth as well as the radiative and chemical characteristics of the upper troposphere. A recent observational study documented an electrified pyrocumulus over the May 2012 Hewlett Gulch fire located to the west of Fort Collins, Colorado. This cloud produced approximately 20 intracloud lightning flashes, and its electrical activity differed from surrounding convection that was not directly impacted by the fire and associated smoke. The goal of this research is to investigate aerosol-induced cloud-scale microphysical differences between clean clouds and polluted pyrocumulus to better characterize the mechanisms that cause pyrocumulus electrification. In order to address this goal, idealized cloud-resolving model simulations were performed using the Regional Atmospheric Modeling System (RAMS). The model environment was initialized with an average of the 12Z 16 May and 00Z 17 May 2012 observed Denver soundings to represent the conditions when the Hewlett Gulch pyrocumulus occurred. Five simulations were performed using surface aerosol concentrations from 100 to 5000 #/mg. The results demonstrate that in moderately polluted pyrocumulus, rain processes are suppressed while graupel production increases. Extremely polluted pyrocumulus, however, experience a complete shut-down of graupel production, which favors the production of large amounts of liquid water and smaller ice species such as ice crystals and snowflakes. The processes responsible for these microphysical changes, as well as inferred pyrocumulus electrification mechanisms, will be compared with those discussed in previous observational studies of this case.

Retrieval of cloud properties from POLDER-3 data using the neural network approach

NASA Astrophysics Data System (ADS)

Di Noia, A.; Hasekamp, O. P.

2017-12-01

Satellite multi-angle spectroplarimetry is a useful technique for observing the microphysical properties of clouds and aerosols. Most of the algorithms for the retrieval of cloud and aerosol properties from satellite measurements require multiple calls to radiative transfer models, which make the retrieval computationally expensive. A traditional alternative to these schemes is represented by lookup-tables (LUTs), where the retrieval is performed by choosing, within a predefined database of combinations of clouds or aerosol properties, the combination that best fits the measurements. LUT retrievals are quicker than full-physics, iterative retrievals, but their accuracy is limited by the number of entries stored in the LUT. Another retrieval method capable of producing very quick retrievals without a big sacrifice in accuracy is the neural network method. Neural network methods are routinely applied to several types of satellite measurements, but their application to multi-angle spectropolarimetric data is still in its early stage, because of the difficulty of accounting for the angular variability of the measurements in the training process. We have recently developed a neural network scheme for the retrieval of cloud properties from POLDER-3 data. The neural network retrieval is trained using synthetic measurements performed for realistic combinations of cloud properties and measurement angles, and is able to process an entire orbit in about 20 seconds. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products during one year show encouraging retrieval performance for cloud optical thickness and effective radius. A discussion of the setup of the neural network and of the validation results will be the main topic of our presentation.

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

NASA Astrophysics Data System (ADS)

van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.

2017-12-01

Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

Fresh clouds: A parameterized updraft method for calculating cloud densities in one-dimensional models

NASA Astrophysics Data System (ADS)

Wong, Michael H.; Atreya, Sushil K.; Kuhn, William R.; Romani, Paul N.; Mihalka, Kristen M.

2015-01-01

Models of cloud condensation under thermodynamic equilibrium in planetary atmospheres are useful for several reasons. These equilibrium cloud condensation models (ECCMs) calculate the wet adiabatic lapse rate, determine saturation-limited mixing ratios of condensing species, calculate the stabilizing effect of latent heat release and molecular weight stratification, and locate cloud base levels. Many ECCMs trace their heritage to Lewis (Lewis, J.S. [1969]. Icarus 10, 365-378) and Weidenschilling and Lewis (Weidenschilling, S.J., Lewis, J.S. [1973]. Icarus 20, 465-476). Calculation of atmospheric structure and gas mixing ratios are correct in these models. We resolve errors affecting the cloud density calculation in these models by first calculating a cloud density rate: the change in cloud density with updraft length scale. The updraft length scale parameterizes the strength of the cloud-forming updraft, and converts the cloud density rate from the ECCM into cloud density. The method is validated by comparison with terrestrial cloud data. Our parameterized updraft method gives a first-order prediction of cloud densities in a “fresh” cloud, where condensation is the dominant microphysical process. Older evolved clouds may be better approximated by another 1-D method, the diffusive-precipitative Ackerman and Marley (Ackerman, A.S., Marley, M.S. [2001]. Astrophys. J. 556, 872-884) model, which represents a steady-state equilibrium between precipitation and condensation of vapor delivered by turbulent diffusion. We re-evaluate observed cloud densities in the Galileo Probe entry site (Ragent, B. et al. [1998]. J. Geophys. Res. 103, 22891-22910), and show that the upper and lower observed clouds at ∼0.5 and ∼3 bars are consistent with weak (cirrus-like) updrafts under conditions of saturated ammonia and water vapor, respectively. The densest observed cloud, near 1.3 bar, requires unexpectedly strong updraft conditions, or higher cloud density rates. The cloud density rate in this layer may be augmented by a composition with non-NH4SH components (possibly including adsorbed NH3).

Thermodynamics in the Suppressed Phase of the Madden-Julian Oscillation Using a Multiplatform Strategy

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne; Taylor, Patrick

2014-01-01

The Madden-Julian Oscillation (MJO) represents a prominent mode of intraseasonal tropical variability. It is manifest by coherent large-scale changes in atmospheric circulation, convection, and thermodynamic processes. Preconditioning of the environment prior to the active phase of the MJO has been noted, but the balance of theorized mechanisms to accomplish this process remains unresolved. Further, there is a lack of consensus on the means by which primary initiation of an MJO event occurs. Observational and modeling efforts have recently been undertaken to advance our understanding of the physical underpinnings governing MJO development. However these intensive studies are often limited in space and/or time and are potentially subject to model deficiencies. Satellite observations, especially those providing vertical resolution of temperature and moisture, provide an opportunity to expand our knowledge of processes critical to MJO initiation and preconditioning. This work will provide an analysis of suppressed phase thermodynamics with an emphasis on the use of a complementary suite of satellite observations including AIRS/AMSU-A profiles, CERES radiative fluxes, and cloud properties observed by MODIS. Emphasis of this work will regard the distribution of cloud regimes, their radiative-convective effects, and their relationship to moist static energy during the recharge and suppressed stages of MJO initiation and eastward propagation. The analyses will make use of cloud regimes from MODIS observations to provide a compositing technique that enables the identification of systematic connections between different cloud regimes and the larger scale environment. Within these cloud regimes, the relationship between the associated cloud-radiative effects observed by CERES, vertically-resolved and vertically-integrated thermodynamics using AIRS/AMSU-A observations, and atmospheric boundary layer fluxes will be demonstrated.

Observational Approach to Molecular Cloud Evolutation with the Submillimeter-Wave CI Lines

NASA Astrophysics Data System (ADS)

Oka, T.; Yamamoto, S.

Neutral carbon atoms (CI) play important roles both in chemistry and cooling processes of interstellar molecular clouds. It is thus crucial to explore its large area distribution to obtain information on formation processes and thermal balance of molecular clouds. However, observations of the submillimeter-wave CI lines have been limited to small areas around some representative objects. We have constructed a 1.2 m submillimeter-wave telescope at the summit of Mt.Fuji. The telescope was designed for the exclusive use of surveying molecular clouds in two submillimeter-wave CI lines, 3 P1 -3 P0 (492GHz) and 3 P2 -3 P1 (809 GHz), of atomic carbon. A superconductor-insulator-superconductor (SIS) mixer receiver was equipped on the Nasmyth focus of the telescope. The receiver noise temperatures [Trx(DSB)] are 300 K and 1000 K for the 492 GHz and the 809 GHz mixers, respectively. The intermediate frequency is centered at 2 GHz, having a 700 MHz bandwidth. An acousto-optical spectrometer (AOS) with 1024 channel outputs is used as a receiver backend. The telescope was installed at Nishi-yasugawara (alt. 3725 m), which is 200 m north of the highest peak, Kengamine (3776 m), in July 1998. It has b en operatede successfully during 4 observing seasons in a remote way from the Hongo campus of the University of Tokyo. We have already observed more than 40 square degrees of the sky with the CI 492 GHz line. The distribution of CI emission is found to be different from those of the 13 CO or C1 8 O emission in some clouds. These differences are discussed in relation to formation processes of molecular clouds.

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

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

Xu, Kuan-Man; Cheng, Anning

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation andmore » stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.« less

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

DOE PAGES

Xu, Kuan-Man; Cheng, Anning

2016-11-15

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation andmore » stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.« less

The Q Continuum: Encounter with the Cloud Mask

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Philips, C.; Dutcher, S.

2017-12-01

We are developing a common cloud mask for MODIS and VIIRS observations, referred to as the MODIS VIIRS Continuity Mask (MVCM). Our focus is on extending the MODIS-heritage cloud detection approach in order to generate appropriate climate data records for clouds and climate studies. The MVCM is based on heritage from the MODIS cloud mask (MOD35 and MYD35) and employs a series of tests on MODIS reflectances and brightness temperatures. Cloud detection is based on contrasts (i.e., cloud versus background surface) at pixel resolution. The MVCM follows the same approach. These cloud masks use multiple cloud detection tests to indicate the confidence level that the observation is of a clear-sky scene. The outcome of a test ranges from 0 (cloudy) to 1 (clear-sky scene). Because of overlap in the sensitivities of the various spectral tests to the type of cloud, each test is considered in one of several groups. The final cloud mask is determined from the product of the minimum confidence of each group and is referred to as the Q value as defined in Ackerman et al (1998). In MOD35 and MYD35 processing, the Q value is not output, rather predetermined Q values determine the result: If Q ≥ .99 the scene is clear; .95 ≤ Q < .99 the pixel is probably a clear scene, .66 ≤ Q < .95 is probably cloudy and Q < .66 is cloudy. Thus representing Q discretely and not as a continuum. For the MVCM, the numerical value of the Q is output along with the classification of clear, probably clear, probably cloudy, and cloudy. Through comparisons with collocated CALIOP and MODIS observations, we will assess the categorization of the Q values as a function of scene type ). While validation studies have indicated the utility and statistical correctness of the cloud mask approach, the algorithm does not possess immeasurable power and perfection. This comparison will assess the time and space dependence of Q and assure that the laws of physics are followed, at least according to normal human notions. Using CALIOP as representing truth, a receiver operating characteristic curve (ROC) will be analyzed to determine the optimum Q for various scenes and seasons, thus providing a continuum of discriminating thresholds.

Partitioning the primary ice formation modes in large eddy simulations of mixed-phase clouds

NASA Astrophysics Data System (ADS)

Hande, Luke B.; Hoose, Corinna

2017-11-01

State-of-the-art aerosol-dependent parameterisations describing each heterogeneous ice nucleation mode (contact, immersion, and deposition ice nucleation), as well as homogeneous nucleation, were incorporated into a large eddy simulation model. Several cases representing commonly occurring cloud types were simulated in an effort to understand which ice nucleation modes contribute the most to total concentrations of ice crystals. The cases include a completely idealised warm bubble, semi-idealised deep convection, an orographic cloud, and a stratiform case. Despite clear differences in thermodynamic conditions between the cases, the results are remarkably consistent between the different cloud types. In all the investigated cloud types and under normal aerosol conditions, immersion freezing dominates and contact freezing also contributes significantly. At colder temperatures, deposition nucleation plays only a small role, and homogeneous freezing is important. To some extent, the temporal evolution of the cloud determines the dominant freezing mechanism and hence the subsequent microphysical processes. Precipitation is not correlated with any one ice nucleation mode, instead occurring simultaneously when several nucleation modes are active. Furthermore, large variations in the aerosol concentration do affect the dominant ice nucleation mode; however, they have only a minor influence on the precipitation amount.

Utilizing the Iterative Closest Point (ICP) algorithm for enhanced registration of high resolution surface models - more than a simple black-box application

NASA Astrophysics Data System (ADS)

Stöcker, Claudia; Eltner, Anette

2016-04-01

Advances in computer vision and digital photogrammetry (i.e. structure from motion) allow for fast and flexible high resolution data supply. Within geoscience applications and especially in the field of small surface topography, high resolution digital terrain models and dense 3D point clouds are valuable data sources to capture actual states as well as for multi-temporal studies. However, there are still some limitations regarding robust registration and accuracy demands (e.g. systematic positional errors) which impede the comparison and/or combination of multi-sensor data products. Therefore, post-processing of 3D point clouds can heavily enhance data quality. In this matter the Iterative Closest Point (ICP) algorithm represents an alignment tool which iteratively minimizes distances of corresponding points within two datasets. Even though tool is widely used; it is often applied as a black-box application within 3D data post-processing for surface reconstruction. Aiming for precise and accurate combination of multi-sensor data sets, this study looks closely at different variants of the ICP algorithm including sub-steps of point selection, point matching, weighting, rejection, error metric and minimization. Therefore, an agricultural utilized field was investigated simultaneously by terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) sensors two times (once covered with sparse vegetation and once bare soil). Due to different perspectives both data sets show diverse consistency in terms of shadowed areas and thus gaps so that data merging would provide consistent surface reconstruction. Although photogrammetric processing already included sub-cm accurate ground control surveys, UAV point cloud exhibits an offset towards TLS point cloud. In order to achieve the transformation matrix for fine registration of UAV point clouds, different ICP variants were tested. Statistical analyses of the results show that final success of registration and therefore data quality depends particularly on parameterization and choice of error metric, especially for erroneous data sets as in the case of sparse vegetation cover. At this, the point-to-point metric is more sensitive to data "noise" than the point-to-plane metric which results in considerably higher cloud-to-cloud distances. Concluding, in order to comply with accuracy demands of high resolution surface reconstruction and the aspect that ground control surveys can reach their limits both in time exposure and terrain accessibility ICP algorithm represents a great tool to refine rough initial alignment. Here different variants of registration modules allow for individual application according to the quality of the input data.

New particle dependant parameterizations of heterogeneous freezing processes.

NASA Astrophysics Data System (ADS)

Diehl, Karoline; Mitra, Subir K.

2014-05-01

For detailed investigations of cloud microphysical processes an adiabatic air parcel model with entrainment is used. It represents a spectral bin model which explicitly solves the microphysical equations. The initiation of the ice phase is parameterized and describes the effects of different types of ice nuclei (mineral dust, soot, biological particles) in immersion, contact, and deposition modes. As part of the research group INUIT (Ice Nuclei research UnIT), existing parameterizations have been modified for the present studies and new parameterizations have been developed mainly on the basis of the outcome of INUIT experiments. Deposition freezing in the model is dependant on the presence of dry particles and on ice supersaturation. The description of contact freezing combines the collision kernel of dry particles with the fraction of frozen drops as function of temperature and particle size. A new parameterization of immersion freezing has been coupled to the mass of insoluble particles contained in the drops using measured numbers of ice active sites per unit mass. Sensitivity studies have been performed with a convective temperature and dew point profile and with two dry aerosol particle number size distributions. Single and coupled freezing processes are studied with different types of ice nuclei (e.g., bacteria, illite, kaolinite, feldspar). The strength of convection is varied so that the simulated cloud reaches different levels of temperature. As a parameter to evaluate the results the ice water fraction is selected which is defined as the relation of the ice water content to the total water content. Ice water fractions between 0.1 and 0.9 represent mixed-phase clouds, larger than 0.9 ice clouds. The results indicate the sensitive parameters for the formation of mixed-phase and ice clouds are: 1. broad particle number size distribution with high number of small particles, 2. temperatures below -25°C, 3. specific mineral dust particles as ice nuclei such as illite or montmorillonite. Coupled cases of deposition and contact freezing show that they are hardly in competition because of differences in the preferred particle sizes. In the contact mode, small particles are less efficient for collisions as well as less efficient as ice nuclei so that these are available for deposition freezing. On the other hand, immersion freezing is the dominant process when it is coupled with deposition freezing. As it is initiated earlier the formed ice particles consume water vapor for growing. The competition of combined contact and immersion freezing leads to lower ice water contents because more ice particles are formed via the immersion mode. In general, ice clouds and mixed-phase clouds with high ice water fractions are not directly the result of primary ice formation but of secondary ice formation and growth of ice particles at the expense of liquid drops.

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model

PubMed Central

Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J.; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H.; Molina, Mario J.

2014-01-01

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol–climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by −2.5 and +1.3 W m−2, respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors’ knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale. PMID:24733923

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model.

PubMed

Wang, Yuan; Wang, Minghuai; Zhang, Renyi; Ghan, Steven J; Lin, Yun; Hu, Jiaxi; Pan, Bowen; Levy, Misti; Jiang, Jonathan H; Molina, Mario J

2014-05-13

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by -2.5 and +1.3 W m(-2), respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors' knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.

DESPOTIC - a new software library to Derive the Energetics and SPectra of Optically Thick Interstellar Clouds

NASA Astrophysics Data System (ADS)

Krumholz, Mark R.

2014-01-01

I describe DESPOTIC, a code to Derive the Energetics and SPectra of Optically Thick Interstellar Clouds. DESPOTIC represents such clouds using a one-zone model, and can calculate line luminosities, line cooling rates, and in restricted cases line profiles using an escape probability formalism. It also includes approximate treatments of the dominant heating, cooling and chemical processes for the cold interstellar medium, including cosmic ray and X-ray heating, grain photoelectric heating, heating of the dust by infrared and ultraviolet radiation, thermal cooling of the dust, collisional energy exchange between dust and gas, and a simple network for carbon chemistry. Based on these heating, cooling and chemical rates, DESPOTIC can calculate clouds' equilibrium gas and dust temperatures, equilibrium carbon chemical state and time-dependent thermal and chemical evolution. The software is intended to allow rapid and interactive calculation of clouds' characteristic temperatures, identification of their dominant heating and cooling mechanisms and prediction of their observable spectra across a wide range of interstellar environments. DESPOTIC is implemented as a PYTHON package, and is released under the GNU General Public License.

Full-Time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instruments and Data Analysis

NASA Technical Reports Server (NTRS)

Campbell, James R.; Hlavka, Dennis L.; Welton, Ellsworth J.; Flynn, Connor J.; Turner, David D.; Spinhirne, James D.; Scott, V. Stanley, III; Hwang, I. H.; Einaudi, Franco (Technical Monitor)

2001-01-01

Atmospheric radiative forcing, surface radiation budget, and top of the atmosphere radiance interpretation involves a knowledge of the vertical height structure of overlying cloud and aerosol layers. During the last decade, the U.S. Department of Energy through I the Atmospheric Radiation Measurement (ARM) program has constructed four long- term atmospheric observing sites in strategic climate regimes (north central Oklahoma, In Barrow. Alaska, and Nauru and Manus Islands in the tropical western Pacific). Micro Pulse Lidar (MPL) systems provide continuous, autonomous observation of all significant atmospheric cloud and aerosol at each of the central ARM facilities. Systems are compact and transmitted pulses are eye-safe. Eye-safety is achieved by expanding relatively low-powered outgoing Pulse energy through a shared, coaxial transmit/receive telescope. ARM NIPL system specifications, and specific unit optical designs are discussed. Data normalization and calibration techniques are presented. A multiple cloud boundary detection algorithm is also described. These techniques in tandem represent an operational value added processing package used to produce normalized data products for Cloud and aerosol research and the historical ARM data archive.

A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

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

Berg, L. K.; Shrivastava, M.; Easter, R. C.

A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convectivemore » cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as –50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

DOE PAGES

Berg, L. K.; Shrivastava, M.; Easter, R. C.; ...

2015-02-24

A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convectivemore » cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as –50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.« less

Extratropical Cyclone in the Southern Ocean

NASA Technical Reports Server (NTRS)

2001-01-01

These images from the Multi-angle Imaging SpectroRadiometer portray an occluded extratropical cyclone situated in the Southern Ocean, about 650 kilometers south of the Eyre Peninsula, South Australia.

Parts of the Yorke Peninsula and a portion of the Murray-Darling River basin are visible between the clouds near the top of the left-hand image, a true-color view from MISR's nadir(vertical-viewing) camera. Retrieved cloud-tracked wind velocities are indicated by the superimposed arrows. The image on the right displays cloud-top heights. Areas where cloud heights could not be retrieved are shown in black. Both the wind vectors and the cloud heights were derived using data from multiple MISR cameras within automated computer processing algorithms. The stereoscopic algorithms used to generate these results are still being refined, and future versions of these products may show modest changes.

Extratropical cyclones are the dominant weather system at midlatitudes, and the term is used generically for region allow-pressure systems in the mid- to high-latitudes. In the southern hemisphere, cyclonic rotation is clockwise. These storms obtain their energy from temperature differences between air masses on either side of warm and cold fronts, and their characteristic pattern is of warm and cold fronts radiating out from a migrating low pressure center which forms, deepens, and dissipates as the fronts fold and collapse on each other. The center of this cyclone has started to decay, with the band of cloud to the south most likely representing the main front that was originally connected with the cyclonic circulation.

These views were acquired on October 11, 2001 during Terra orbit 9650, and represent an area of about 380 kilometers x 1900 kilometers.

Extratropical Cyclone in the Southern Ocean

NASA Technical Reports Server (NTRS)

2002-01-01

These images from the Multi-angle Imaging SpectroRadiometer (MISR) portray an occluded extratropical cyclone situated in the Southern Ocean, about 650 kilometers south of the Eyre Peninsula, South Australia. The left-hand image, a true-color view from MISR's nadir (vertical-viewing) camera, shows clouds just south of the Yorke Peninsula and the Murray-Darling river basin in Australia. Retrieved cloud-tracked wind velocities are indicated by the superimposed arrows. The image on the right displays cloud-top heights. Areas where cloud heights could not be retrieved are shown in black. Both the wind vectors and the cloud heights were derived using data from multiple MISR cameras within automated computer processing algorithms. The stereoscopic algorithms used to generate these results are still being refined, and future versions of these products may show modest changes. Extratropical cyclones are the dominant weather system at midlatitudes, and the term is used generically for regional low-pressure systems in the mid- to high-latitudes. In the southern hemisphere, cyclonic rotation is clockwise. These storms obtain their energy from temperature differences between air masses on either side of warm and cold fronts, and their characteristic pattern is of warm and cold fronts radiating out from a migrating low pressure center which forms, deepens, and dissipates as the fronts fold and collapse on each other. The center of this cyclone has started to decay, with the band of cloud to the south most likely representing the main front that was originally connected with the cyclonic circulation. These views were acquired on October 11, 2001, and the large view represents an area of about 380 kilometers x 1900 kilometers. Image courtesy NASA/GSFC/LaRC/JPL, MISR Team.

Cloud Condensation Nuclei Activity of Aerosols during GoAmazon 2014/15 Field Campaign Report

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

Wang, J.; Martin, S. T.; Kleinman, L.

2016-03-01

Aerosol indirect effects, which represent the impact of aerosols on climate through influencing the properties of clouds, remain one of the main uncertainties in climate predictions (Stocker et al. 2013). Reducing this large uncertainty requires both improved understanding and representation of aerosol properties and processes in climate models, including the cloud activation properties of aerosols. The Atmospheric System Research (ASR) science program plan of January 2010 states that: “A key requirement for simulating aerosol-cloud interactions is the ability to calculate cloud condensation nuclei and ice nuclei (CCN and IN, respectively) concentrations as a function of supersaturation from the chemical andmore » microphysical properties of the aerosol.” The Observations and Modeling of the Green Ocean Amazon (GoAmazon 2014/15) study seeks to understand how aerosol and cloud life cycles are influenced by pollutant outflow from a tropical megacity (Manaus)—in particular, the differences in cloud-aerosol-precipitation interactions between polluted and pristine conditions. One key question of GoAmazon2014/5 is: “What is the influence of the Manaus pollution plume on the cloud condensation nuclei (CCN) activities of the aerosol particles and the secondary organic material in the particles?” To address this question, we measured size-resolved CCN spectra, a critical measurement for GoAmazon2014/5.« less

Comparisons of Cloud Properties over the Southern Ocean between In situ Observations and WRF Simulations

NASA Astrophysics Data System (ADS)

D'Alessandro, J.; Diao, M.; Wu, C.; Liu, X.

2017-12-01

Numerical weather models often struggle at representing clouds since small scale cloud processes must be parameterized. For example, models often utilize simple parameterizations for transitioning from liquid to ice, usually set as a function of temperature. However, supercooled liquid water (SLW) often persists at temperatures much lower than threshold values used in microphysics parameterizations. Previous observational studies of clouds over the Southern Ocean have found high frequencies of SLW (e.g., Morrison et al., 2011). Many of these studies have relied on satellite retrievals, which provide relatively low resolution observations and are often associated with large uncertainties due to assumptions of microphysical properties (e.g., particle size distributions). Recently, the NSF/NCAR O2/N2 Ratio and CO2 Airborne Southern Ocean Study (ORCAS) campaign took observations via the NSF/NCAR HIAPER research aircraft during January and February of 2016, providing in situ observations over the Southern Ocean (50°W to 92°W). We compare simulated results from the Weather Research and Forecasting (WRF) model with in situ observations from ORCAS. Differences between observations and simulations are evaluated via statistical analyses. Initial results from ORCAS reveal a high frequency of SLW at temperatures as low as -15°C, and the existence of SLW around -30°C. Recent studies have found that boundary layer clouds are underestimated by WRF in regions unaffected by cyclonic activity (Huang et al., 2014), suggesting a lack of low-level moisture due to local processes. To explore this, relative humidity distributions are examined and controlled by cloud microphysical characteristics (e.g., total water content) and relevant ambient properties (e.g., vertical velocity). A relatively low frequency of simulated SLW may in part explain the discrepancies in WRF, as cloud-top SLW results in stronger radiative cooling and turbulent motions conducive for long-lived cloud regimes. Results presented in this study will help improve our understanding of Southern Ocean clouds and the observed discrepancies seen in WRF simulations.

The representation of low-level clouds during the West African monsoon in weather and climate models

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and radiation data) and ground-based eye observations of clouds and radiation measurements from weather stations. Our results show that many of the climate models have great difficulties representing the diurnal cycle of winds and clouds, leading to associated errors in radiation. Typical errors include a substantial underestimation of the lowest clouds accompanied by an overestimation of clouds at the top of the monsoon layer, indicating systematic problems in vertical exchange processes, which are also reflected in large errors in jet speed. Consequently, many models show a too flat diurnal cycle in cloudiness. This contribution is part of the EU-funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project that aims to investigate the impact of the drastic increase in anthropogenic emissions in West Africa on the local weather and climate, for example through cloud-aerosol interactions. The analysis of the capability of state-of-the-art numerical models to represent low-level cloudiness presented here is an important requisite for the planned assessments of the influence of anthropogenic aerosol.

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

PubMed Central

Schmale, Julia; Henning, Silvia; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Bougiatioti, Aikaterini; Kalivitis, Nikos; Stavroulas, Iasonas; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Kristensson, Adam; Iwamoto, Yoko; Pringle, Kirsty; Reddington, Carly; Aalto, Pasi; Äijälä, Mikko; Baltensperger, Urs; Bialek, Jakub; Birmili, Wolfram; Bukowiecki, Nicolas; Ehn, Mikael; Fjæraa, Ann Mari; Fiebig, Markus; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Furuya, Masaki; Hammer, Emanuel; Heikkinen, Liine; Herrmann, Erik; Holzinger, Rupert; Hyono, Hiroyuki; Kanakidou, Maria; Kiendler-Scharr, Astrid; Kinouchi, Kento; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Motos, Ghislain; Nenes, Athanasios; O’Dowd, Colin; Paramonov, Mikhail; Petäjä, Tuukka; Picard, David; Poulain, Laurent; Prévôt, André Stephan Henry; Slowik, Jay; Sonntag, Andre; Swietlicki, Erik; Svenningsson, Birgitta; Tsurumaru, Hiroshi; Wiedensohler, Alfred; Wittbom, Cerina; Ogren, John A.; Matsuki, Atsushi; Yum, Seong Soo; Myhre, Cathrine Lund; Carslaw, Ken; Stratmann, Frank; Gysel, Martin

2017-01-01

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment. PMID:28291234

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

NASA Astrophysics Data System (ADS)

Schmale, Julia; Henning, Silvia; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Bougiatioti, Aikaterini; Kalivitis, Nikos; Stavroulas, Iasonas; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Kristensson, Adam; Iwamoto, Yoko; Pringle, Kirsty; Reddington, Carly; Aalto, Pasi; Äijälä, Mikko; Baltensperger, Urs; Bialek, Jakub; Birmili, Wolfram; Bukowiecki, Nicolas; Ehn, Mikael; Fjæraa, Ann Mari; Fiebig, Markus; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Furuya, Masaki; Hammer, Emanuel; Heikkinen, Liine; Herrmann, Erik; Holzinger, Rupert; Hyono, Hiroyuki; Kanakidou, Maria; Kiendler-Scharr, Astrid; Kinouchi, Kento; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Motos, Ghislain; Nenes, Athanasios; O'Dowd, Colin; Paramonov, Mikhail; Petäjä, Tuukka; Picard, David; Poulain, Laurent; Prévôt, André Stephan Henry; Slowik, Jay; Sonntag, Andre; Swietlicki, Erik; Svenningsson, Birgitta; Tsurumaru, Hiroshi; Wiedensohler, Alfred; Wittbom, Cerina; Ogren, John A.; Matsuki, Atsushi; Yum, Seong Soo; Myhre, Cathrine Lund; Carslaw, Ken; Stratmann, Frank; Gysel, Martin

2017-03-01

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.

Cloud-edge mixing: Direct numerical simulation and observations in Indian Monsoon clouds

NASA Astrophysics Data System (ADS)

Kumar, Bipin; Bera, Sudarsan; Prabha, Thara V.; Grabowski, Wojceich W.

2017-03-01

A direct numerical simulation (DNS) with the decaying turbulence setup has been carried out to study cloud-edge mixing and its impact on the droplet size distribution (DSD) applying thermodynamic conditions observed in monsoon convective clouds over Indian subcontinent during the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). Evaporation at the cloud-edges initiates mixing at small scale and gradually introduces larger-scale fluctuations of the temperature, moisture, and vertical velocity due to droplet evaporation. Our focus is on early evolution of simulated fields that show intriguing similarities to the CAIPEEX cloud observations. A strong dilution at the cloud edge, accompanied by significant spatial variations of the droplet concentration, mean radius, and spectral width, are found in both the DNS and in observations. In DNS, fluctuations of the mean radius and spectral width come from the impact of small-scale turbulence on the motion and evaporation of inertial droplets. These fluctuations decrease with the increase of the volume over which DNS data are averaged, as one might expect. In cloud observations, these fluctuations also come from other processes, such as entrainment/mixing below the observation level, secondary CCN activation, or variations of CCN activation at the cloud base. Despite large differences in the spatial and temporal scales, the mixing diagram often used in entrainment/mixing studies with aircraft data is remarkably similar for both DNS and cloud observations. We argue that the similarity questions applicability of heuristic ideas based on mixing between two air parcels (that the mixing diagram is designed to properly represent) to the evolution of microphysical properties during turbulent mixing between a cloud and its environment.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Measurement Comparisons Towards Improving the Understanding of Aerosol-Cloud Processing

NASA Astrophysics Data System (ADS)

Noble, Stephen R.

Cloud processing of aerosol is an aerosol-cloud interaction that is not heavily researched but could have implications on climate. The three types of cloud processing are chemical processing, collision and coalescence processing, and Brownian capture of interstitial particles. All types improve cloud condensation nuclei (CCN) in size or hygroscopicity (kappa). These improved CCN affect subsequent clouds. This dissertation focuses on measurement comparisons to improve our observations and understanding of aerosol-cloud processing. Particle size distributions measured at the continental Southern Great Plains (SGP) site were compared with ground based measurements of cloud fraction (CF) and cloud base altitude (CBA). Particle size distributions were described by a new objective shape parameter to define bimodality rather than an old subjective one. Cloudy conditions at SGP were found to be correlated with lagged shape parameter. Horizontal wind speed and regional CF explained 42%+ of this lag time. Many of these surface particle size distributions were influenced by aerosol-cloud processing. Thus, cloud processing may be more widespread with more implications than previously thought. Particle size distributions measured during two aircraft field campaigns (MArine Stratus/stratocumulus Experiment; MASE; and Ice in Cloud Experiment-Tropical; ICE-T) were compared to CCN distributions. Tuning particle size to critical supersaturation revealed hygroscopicity expressed as ? when the distributions were overlain. Distributions near cumulus clouds (ICE-T) had a higher frequency of the same ?s (48% in ICE-T to 42% in MASE) between the accumulation (processed) and Aitken (unprocessed) modes. This suggested physical processing domination in ICE-T. More MASE (stratus cloud) kappa differences between modes pointed to chemical cloud processing. Chemistry measurements made in MASE showed increases in sulfates and nitrates with distributions that were more processed. This supported chemical cloud processing in MASE. This new method to determine kappa provides the needed information without interrupting ambient measurements. MODIS derived cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (re) were compared to the same in situ derived variables from cloud probe measurements of two stratus/stratocumulus cloud campaigns (MASE and Physics Of Stratocumulus Tops; POST). In situ data were from complete vertical cloud penetrations, while MODIS data were from pixels along the aircraft penetration path. Comparisons were well correlated except that MODIS LWP (14-36%) and re (20-30%) were biased high. The LWP bias was from re bias and was not improved by using the vertically stratified assumption. MODIS re bias was almost removed when compared to cloud top maximum in situ re, but, that does not describe re for the full depth of the cloud. COT is validated by in situ COT. High correlations suggest that MODIS variables are useful in self-comparisons such as gradient changes in stratus cloud re during aerosol-cloud processing.

An Assessment of New Satellite Data Products for the Development of a Long-Term Global Solar Resource at 10-100 km

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

Stackhouse Jr., Paul W.; Minnis, Patrick; Perez, Richard

A project representing an effort to reprocess the NASA based solar resource data sets is reviewed. The effort represented a collaboration between NASA, NOAA, NREL and the SUNY-Albany and aimed to deliver a 10 km resolution, 3-hourly data set spanning from 1983 through near-present. Part of the project was to transition project capability to NREL for annual processing to extend data set. Due to delays in the key input project called ISCCP, we evaluate only Beta versions of this data set and also introduce the potential use of another NASA Langley based cloud data set for the CERES project. Themore » CERES project uses these cloud properties to compute global top-of-atmosphere and surface fluxes at the 1x1 degree resolution. Here, we also briefly discuss these data sets in potential usage for solar resource benchmarking.« less

An Assessment of New Satellite Data Products for the Development of a Long-Term Global Solar Resource at 10-100 km

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Minnis, Patrick; Perez, Richard; Sengupta, Manajit; Knapp, Kenneth; Mikovitz, J. Colleen; Schlemmer, James; Scarino, Benjamin; Zhang, Taiping; Cox, Stephen J.

2016-01-01

A project representing an effort to reprocess the NASA based solar resource data sets is reviewed. The effort represented a collaboration between NASA, NOAA, NREL and the SUNY-Albany and aimed to deliver a 10 km resolution, 3-hourly data set spanning from 1983 through near-present. Part of the project was to transition project capability to NREL for annual processing to extend data set. Due to delays in the key input project called ISCCP, we evaluate only Beta versions of this data set and also introduce the potential use of another NASA Langley based cloud data set for the CERES project. The CERES project uses these cloud properties to compute global top-of-atmosphere and surface fluxes at the 1x1 degree resolution. Here, we also briefly discuss these data sets in potential usage for solar resource benchmarking.

Observations of fluorescent aerosol-cloud interactions in the free troposphere at the Sphinx high Alpine research station, Jungfraujoch

NASA Astrophysics Data System (ADS)

Crawford, I.; Lloyd, G.; Bower, K. N.; Connolly, P. J.; Flynn, M. J.; Kaye, P. H.; Choularton, T. W.; Gallagher, M. W.

2015-09-01

The fluorescent nature of aerosol at a high Alpine site was studied using a wide-band integrated bioaerosol (WIBS-4) single particle multi-channel ultra violet-light induced fluorescence (UV-LIF) spectrometer. This was supported by comprehensive cloud microphysics and meteorological measurements with the aims of cataloguing concentrations of bio-fluorescent aerosols at this high altitude site and also investigating possible influences of UV-fluorescent particle types on cloud-aerosol processes. Analysis of background free tropospheric air masses, using a total aerosol inlet, showed there to be a minor but statistically insignificant increase in the fluorescent aerosol fraction during in-cloud cases compared to out of cloud cases. The size dependence of the fluorescent aerosol fraction showed the larger aerosol to be more likely to be fluorescent with 80 % of 10 μm particles being fluorescent. Whilst the fluorescent particles were in the minority (NFl/NAll = 0.27±0.19), a new hierarchical agglomerative cluster analysis approach, Crawford et al. (2015) revealed the majority of the fluorescent aerosol were likely to be representative of fluorescent mineral dust. A minor episodic contribution from a cluster likely to be representative of primary biological aerosol particles (PBAP) was also observed with a wintertime baseline concentration of 0.1±0.4 L-1. Given the low concentration of this cluster and the typically low ice active fraction of studied PBAP (e.g. pseudomonas syringae) we suggest that the contribution to the observed ice crystal concentration at this location is not significant during the wintertime.

Determinants of Low Cloud Properties - An Artificial Neural Network Approach Using Observation Data Sets

NASA Astrophysics Data System (ADS)

Andersen, Hendrik; Cermak, Jan

2015-04-01

This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.

Physical Validation of GPM Retrieval Algorithms Over Land: An Overview of the Mid-Latitude Continental Convective Clouds Experiment (MC3E)

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Jensen, Michael P.

2011-01-01

The joint NASA Global Precipitation Measurement (GPM) -- DOE Atmospheric Radiation Measurement (ARM) Midlatitude Continental Convective Clouds Experiment (MC3E) was conducted from April 22-June 6, 2011, centered on the DOE-ARM Southern Great Plains Central Facility site in northern Oklahoma. GPM field campaign objectives focused on the collection of airborne and ground-based measurements of warm-season continental precipitation processes to support refinement of GPM retrieval algorithm physics over land, and to improve the fidelity of coupled cloud resolving and land-surface satellite simulator models. DOE ARM objectives were synergistically focused on relating observations of cloud microphysics and the surrounding environment to feedbacks on convective system dynamics, an effort driven by the need to better represent those interactions in numerical modeling frameworks. More specific topics addressed by MC3E include ice processes and ice characteristics as coupled to precipitation at the surface and radiometer signals measured in space, the correlation properties of rainfall and drop size distributions and impacts on dual-frequency radar retrieval algorithms, the transition of cloud water to rain water (e.g., autoconversion processes) and the vertical distribution of cloud water in precipitating clouds, and vertical draft structure statistics in cumulus convection. The MC3E observational strategy relied on NASA ER-2 high-altitude airborne multi-frequency radar (HIWRAP Ka-Ku band) and radiometer (AMPR, CoSMIR; 10-183 GHz) sampling (a GPM "proxy") over an atmospheric column being simultaneously profiled in situ by the University of North Dakota Citation microphysics aircraft, an array of ground-based multi-frequency scanning polarimetric radars (DOE Ka-W, X and C-band; NASA D3R Ka-Ku and NPOL S-bands) and wind-profilers (S/UHF bands), supported by a dense network of over 20 disdrometers and rain gauges, all nested in the coverage of a six-station mesoscale rawinsonde network. As an exploratory effort to examine land-surface emissivity impacts on retrieval algorithms, and to demonstrate airborne soil moisture retrieval capabilities, the University of Tennessee Space Institute Piper aircraft carrying the MAPIR L-band radiometer was also flown during the latter half of the experiment in coordination with the ER-2. The observational strategy provided a means to sample the atmospheric column in a redundant framework that enables inter-calibration and constraint of measured and retrieved precipitation characteristics such as particle size distributions, or water contents- all within the umbrella of "proxy" satellite measurements (i.e., the ER-2). Complimenting the precipitation sampling framework, frequent and coincident launches of atmospheric soundings (e.g., 4-8/day) then provided a much larger mesoscale view of the thermodynamic and winds environment, a data set useful for initializing cloud models. The datasets collected represent a variety cloud and precipitation types including isolated cumulus clouds, severe thunderstorms, mesoscale convective systems, and widespread regions of light to moderate stratiform precipitation. We will present the MC3E experiment design, an overview of operations, and a summary of preliminary results.

ARM Research in the Equatorial Western Pacific: A Decade and Counting

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

Long, Charles N.; McFarlane, Sally A.; Del Genio, Anthony D.

2013-05-22

The tropical western Pacific (TWP) is an important climatic region. Strong solar heating, warm sea surface temperatures and the annual progression of the Intertropical Convergence Zone (ITCZ) across this region generate abundant convective systems, which through their effects on the heat and water budgets have a profound impact on global climate and precipitation. To accurately represent tropical cloud systems in models, measurements of tropical clouds, the environment in which they reside, and their impact on the radiation and water budgets are needed. Because of the remote location, ground-based datasets of cloud, atmosphere, and radiation properties from the TWP region havemore » traditionally come primarily from short-term field experiments. While providing extremely useful information on physical processes, these datasets are limited in statistical and climatological information because of their short duration. To provide long-term measurements of the surface radiation budget in the tropics, and the atmospheric properties that affect it, the Atmospheric Radiation Measurement program established a measurement site on Manus Island, Papua New Guinea in 1996 and on the island republic of Nauru in late 1998. These sites provide unique datasets available from more than 10 years of operation in the equatorial western Pacific on Manus and Nauru. We present examples of the scientific use of these datasets including characterization of cloud properties, analysis of cloud radiative forcing, model studies of tropical clouds and processes, and validation of satellite algorithms. We also note new instrumentation recently installed at the Manus site that will expand opportunities for tropical atmospheric science.« less

Vertical profiling of aerosol particles and trace gases over the central Arctic Ocean during summer

NASA Astrophysics Data System (ADS)

Kupiszewski, P.; Leck, C.; Tjernström, M.; Sjogren, S.; Sedlar, J.; Graus, M.; Müller, M.; Brooks, B.; Swietlicki, E.; Norris, S.; Hansel, A.

2013-12-01

Unique measurements of vertical size-resolved aerosol particle concentrations, trace gas concentrations and meteorological data were obtained during the Arctic Summer Cloud Ocean Study (ASCOS, www.ascos.se), an International Polar Year project aimed at establishing the processes responsible for formation and evolution of low-level clouds over the high Arctic summer pack ice. The experiment was conducted from on board the Swedish icebreaker Oden, and provided both ship- and helicopter-based measurements. This study focuses on the vertical helicopter profiles and onboard measurements obtained during a three-week period when Oden was anchored to a drifting ice floe, and sheds light on the characteristics of Arctic aerosol particles and their distribution throughout the lower atmosphere. Distinct differences in aerosol particle characteristics within defined atmospheric layers are identified. Within the lowermost couple hundred metres, transport from the marginal ice zone (MIZ), condensational growth and cloud processing develop the aerosol population. During two of the four representative periods defined in this study, such influence is shown. At altitudes above about 1 km, long-range transport occurs frequently. However, only infrequently does large-scale subsidence descend such air masses to become entrained into the mixed layer in the high Arctic, and therefore long-range transport plumes are unlikely to directly influence low-level stratiform cloud formation. Nonetheless, such plumes can influence the radiative balance of the planetary boundary layer (PBL) by influencing formation and evolution of higher clouds, as well as through precipitation transport of particles downwards. New particle formation was occasionally observed, particularly in the near-surface layer. We hypothesize that the origin of these ultrafine particles could be in biological processes, both primary and secondary, within the open leads between the pack ice and/or along the MIZ. In general, local sources, in combination with upstream boundary-layer transport of precursor gases from the MIZ, are considered to constitute the origin of cloud condensation nuclei (CCN) particles and thus be of importance for the formation of interior Arctic low-level clouds during summer, and subsequently, through cloud influences, for the melting and freezing of sea ice.

77 FR 65177 - Swap Data Repositories: Interpretative Statement Regarding the Confidentiality and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-25

... participation in standard-setting bodies to develop international standards relevant to the swap markets. Cloud Strategix, LLC (``Cloud Strategix''), representing the data hosting and cloud computing industry, in... Roundtable, June 6, 2012; (iii) Cloud Strategix, LLC, June 5, 2012; and (iv) the Depository Trust & Clearing...

The Education Value of Cloud Computing

ERIC Educational Resources Information Center

Katzan, Harry, Jr.

2010-01-01

Cloud computing is a technique for supplying computer facilities and providing access to software via the Internet. Cloud computing represents a contextual shift in how computers are provisioned and accessed. One of the defining characteristics of cloud software service is the transfer of control from the client domain to the service provider.…

Modeling the Cloud to Enhance Capabilities for Crises and Catastrophe Management

DTIC Science & Technology

2016-11-16

order for cloud computing infrastructures to be successfully deployed in real world scenarios as tools for crisis and catastrophe management, where...Statement of the Problem Studied As cloud computing becomes the dominant computational infrastructure[1] and cloud technologies make a transition to hosting...1. Formulate rigorous mathematical models representing technological capabilities and resources in cloud computing for performance modeling and

Get Your Head into the Clouds: Using Word Clouds for Analyzing Qualitative Assessment Data

ERIC Educational Resources Information Center

DePaolo, Concetta A.; Wilkinson, Kelly

2014-01-01

Word clouds (or tag clouds) are popular, fun ways to display text data in graphical form; however, we contend that they can also be useful tools in assessment. Using word clouds, instructors can quickly and easily produce graphical depictions of text representing student knowledge. By investigating the patterns of words or phrases, or lack…

Wide Angle Imaging Lidar (WAIL): Theory of Operation and Results from Cross-Platform Validation at the ARM Southern Great Plains Site

NASA Astrophysics Data System (ADS)

Polonsky, I. N.; Davis, A. B.; Love, S. P.

2004-05-01

WAIL was designed to determine physical and geometrical characteristics of optically thick clouds using the off-beam component of the lidar return that can be accurately modeled within the 3D photon diffusion approximation. The theory shows that the WAIL signal depends not only on the cloud optical characteristics (phase function, extinction and scattering coefficients) but also on the outer thickness of the cloud layer. This makes it possible to estimate the mean optical and geometrical thicknesses of the cloud. The comparison with Monte Carlo simulation demonstrates the high accuracy of the diffusion approximation for moderately to very dense clouds. During operation WAIL is able to collect a complete data set from a cloud every few minutes, with averaging over horizontal scale of a kilometer or so. In order to validate WAIL's ability to deliver cloud properties, the LANL instrument was deployed as a part of the THickness from Off-beam Returns (THOR) validation IOP. The goal was to probe clouds above the SGP CART site at night in March 2002 from below (WAIL and ARM instruments) and from NASA's P3 aircraft (carrying THOR, the GSFC counterpart of WAIL) flying above the clouds. The permanent cloud instruments we used to compare with the results obtained from WAIL were ARM's laser ceilometer, micro-pulse lidar (MPL), millimeter-wavelength cloud radar (MMCR), and micro-wave radiometer (MWR). The comparison shows that, in spite of an unusually low cloud ceiling, an unfavorable observation condition for WAIL's present configuration, cloud properties obtained from the new instrument are in good agreement with their counterparts obtained by other instruments. So WAIL can duplicate, at least for single-layer clouds, the cloud products of the MWR and MMCR together. But WAIL does this with green laser light, which is far more representative than microwaves of photon transport processes at work in the climate system.

Optical instruments synergy in determination of optical depth of thin clouds

NASA Astrophysics Data System (ADS)

Viviana Vlăduţescu, Daniela; Schwartz, Stephen E.; Huang, Dong

2018-04-01

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

Optical Instruments Synergy in Determination of Optical Depth of Thin Clouds

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

Vladutescu, Daniela V.; Schwartz, Stephen E.

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

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

PubMed

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

2017-07-28

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

Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

NASA Astrophysics Data System (ADS)

Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

2018-04-01

A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.

Cost-effective cloud computing: a case study using the comparative genomics tool, roundup.

PubMed

Kudtarkar, Parul; Deluca, Todd F; Fusaro, Vincent A; Tonellato, Peter J; Wall, Dennis P

2010-12-22

Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource-Roundup-using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

The Modification of Orographic Snow Growth Processes by Cloud Nucleating Aerosols

NASA Astrophysics Data System (ADS)

Cotton, W. R.; Saleeby, S.

2011-12-01

Cloud nucleating aerosols have been found to modify the amount and spatial distribution of snowfall in mountainous areas where riming growth of snow crystals is known to contribute substantially to the total snow water equivalent precipitation. In the Park Range of Colorado, a 2km deep supercooled liquid water orographic cloud frequently enshrouds the mountaintop during snowfall events. This leads to a seeder-feeder growth regime in which snow falls through the orographic cloud and collects cloud water prior to surface deposition. The addition of higher concentrations of cloud condensation nuclei (CCN) modifies the cloud droplet spectrum toward smaller size droplets and suppresses riming growth. Without rime growth, the density of snow crystals remains low and horizontal trajectories carry them further downwind due to slower vertical fall speeds. This leads to a downwind shift in snowfall accumulation at high CCN concentrations. Cloud resolving model simulations were performed (at 600m horizontal grid spacing) for six snowfall events over the Park Range. The chosen events were well simulated and occurred during intensive observations periods as part of two winter field campaigns in 2007 and 2010 based at Storm Peak Laboratory in Steamboat Springs, CO. For each event, sensitivity simulations were run with various initial CCN concentration vertical profiles that represent clean to polluted aerosol environments. Microphysical budget analyses were performed for these simulations in order to determine the relative importance of the various cloud properties and growth processes that contribute to precipitation production. Observations and modeling results indicate that initial vapor depositional growth of snow tends to be maximized within about 1km of mountaintop above the windward slope while the majority of riming growth occurs within 500m of mountaintop. This suggests that precipitation production is predominantly driven by locally enhanced orography. The large scale synoptic flow simply provides the background dynamics and moisture that impinge upon the steep terrain. The addition of cloud nucleating aerosols to this scenario tends to reduce the amount of riming and leads to greater snow vapor growth. Increased vapor growth leads to larger snow crystals but does not necessarily increase their density or fall speed. There is frequently a zone on the periphery of the orographic cloud where water saturation is low and ice saturation remains high. Here the Bergeron process allows for snow to continue growing at the expense of the cloud water. Furthermore, since less cloud water is removed by riming, and droplets are smaller in polluted conditions, there is an increase in cloud water evaporation along the lee slope. This enhanced droplet evaporation in polluted conditions allows for more saturated air to persist to the lee of the ridge. Higher saturation reduces the amount of snow crystal sublimation prior to surface deposition. In very moist winter events, the lee slope evaporation relative to the primary mountain barrier can saturate the air relative to a downstream ridge and aid in further orographic cloud development. The combination of reduced riming, the Bergeron process, and reduced lee-side sublimation leads to the snowfall spillover effect under polluted conditions.

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

NASA Astrophysics Data System (ADS)

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

2007-03-01

The double-moment cloud microphysics scheme from ECHAM4 has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass and number concentrations and the aerosol mixing state. This results in a much better agreement with observed vertical profiles of the black carbon and aerosol mass mixing ratios than with the previous version ECHAM4, where only the different aerosol mass mixing ratios were predicted. Also, the simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and -35°C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to -1.8 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and present-day aerosol emissions representative for the year 2000 are used. It is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed.

Numerical experiments on the role of radiative processes in the development and maintenance of upper level clouds

NASA Technical Reports Server (NTRS)

Starr, D. O'C.; Cox, S. K.

1981-01-01

A time-dependent, two-dimensional Eulerian model is presented whose purpose is to obtain more realistic parameterizations of extended high level cloudiness, and the results of a numerical experiment using the model are reported. The model is anelastic and the Bousinesque assumption is invoked. Unresolved subgrid scale processes are parameterized as eddy diffusion processes. Two phases of water are incorporated and equilibrium between them is assumed. The effects of infrared radiative processes are parametrically represented. Two simulations were conducted with identical initial conditions; in one of them, the radiation term was never turned on. The mean values of perturbation potential temperature at each level in the domain are plotted versus height after 15, 30, and 60 minutes of simulated time. The influence of the radiative term is seen to impose a cooling trend, leading to an increased generation of ice water and an increased generation of turbulent kinetic energy in the cloud layer.

Cirrus clouds. I - A cirrus cloud model. II - Numerical experiments on the formation and maintenance of cirrus

NASA Technical Reports Server (NTRS)

Starr, D. OC.; Cox, S. K.

1985-01-01

A simplified cirrus cloud model is presented which may be used to investigate the role of various physical processes in the life cycle of a cirrus cloud. The model is a two-dimensional, time-dependent, Eulerian numerical model where the focus is on cloud-scale processes. Parametrizations are developed to account for phase changes of water, radiative processes, and the effects of microphysical structure on the vertical flux of ice water. The results of a simulation of a thin cirrostratus cloud are given. The results of numerical experiments performed with the model are described in order to demonstrate the important role of cloud-scale processes in determining the cloud properties maintained in response to larger scale forcing. The effects of microphysical composition and radiative processes are considered, as well as their interaction with thermodynamic and dynamic processes within the cloud. It is shown that cirrus clouds operate in an entirely different manner than liquid phase stratiform clouds.

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

Treesearch

Ashley E. Van Beusekom; Grizelle Gonzalez; Martha A. Scholl

2017-01-01

The degree to which cloud immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane cloud forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if cloud base altitude rises as a result of regional warming or deforestation. To establish a baseline...

Open-cell and closed-cell clouds off Peru

NASA Image and Video Library

2010-04-27

2010/107 - 04/17 at 21 :05 UTC. Open-cell and closed-cell clouds off Peru, Pacific Ocean Resembling a frosted window on a cold winter's day, this lacy pattern of marine clouds was captured off the coast of Peru in the Pacific Ocean by the MODIS on the Aqua satellite on April 19, 2010. The image reveals both open- and closed-cell cumulus cloud patterns. These cells, or parcels of air, often occur in roughly hexagonal arrays in a layer of fluid (the atmosphere often behaves like a fluid) that begins to "boil," or convect, due to heating at the base or cooling at the top of the layer. In "closed" cells warm air is rising in the center, and sinking around the edges, so clouds appear in cell centers, but evaporate around cell edges. This produces cloud formations like those that dominate the lower left. The reverse flow can also occur: air can sink in the center of the cell and rise at the edge. This process is called "open cell" convection, and clouds form at cell edges around open centers, which creates a lacy, hollow-looking pattern like the clouds in the upper right. Closed and open cell convection represent two stable atmospheric configurations — two sides of the convection coin. But what determines which path the "boiling" atmosphere will take? Apparently the process is highly chaotic, and there appears to be no way to predict whether convection will result in open or closed cells. Indeed, the atmosphere may sometimes flip between one mode and another in no predictable pattern. Satellite: Aqua NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team To learn more about MODIS go to: rapidfire.sci.gsfc.nasa.gov/gallery/?latest NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe.

Eddy correlation measurements of size-dependent cloud droplet turbulent fluxes to complex terrain

NASA Astrophysics Data System (ADS)

Vong, Richard J.; Kowalski, Andrew S.

1995-07-01

An eddy correlation technique was used to measure the turbulent flux of cloud droplets to complex, forested terrain near the coast of Washington State during the spring of 1993. Excellent agreement was achieved for cloud liquid water content measured by two instruments. Substantial downward liquid water fluxes of 1mm per 24 h were measured at night during "steady and continuous" cloud events, about twice the magnitude of those measured by Beswick etal. in Scotland. Cloud water chemical fluxes were estimated to represent up to 50% of the chemical deposition associated with precipitation at the site. An observed size-dependence in the turbulent liquid water fluxes suggested that both droplet impaction, which leads to downward fluxes, and phase change processes, which can lead to upward fluxes, consistently are important contributors to the eddy correlation results. The diameter below which phase change processes were important to observed fluxes was shown to depend upon σL, the relative standard deviation of the liquid water content (LWC) within a 30-min averaging period. The crossover from upward to downward LW flux occurs at 8µm for steady and continuous cloud events but at 13µm for events with a larger degree of LWC variability. This comparison of the two types of cloud events suggested that evaporation was the most likely cause of upward droplet fluxes for the smaller droplets (dia<13µm) during cloud with variable LWC (σL>0.3).

Microphysical processing of aerosol particles in orographic clouds

NASA Astrophysics Data System (ADS)

Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.

2015-01-01

An explicit and detailed treatment of cloud-borne particles allowing for the consideration of aerosol cycling in clouds has been implemented in the regional weather forecast and climate model COSMO. The effects of aerosol scavenging, cloud microphysical processing and regeneration upon cloud evaporation on the aerosol population and on subsequent cloud formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic cloud. The results allowed to identify different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase cloud, aerosol mass is incorporated into cloud droplets by activation scavenging and released back to the atmosphere upon cloud droplet evaporation. In the mixed-phase cloud, a first cycle comprises cloud droplet activation and evaporation via the Wegener-Bergeron-Findeisen process. A second cycle includes below-cloud scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from cloud droplets to snow flakes. In the simulated mixed-phase cloud, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snow flakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. However, the processes not only impact the total aerosol number and mass, but also the shape of the aerosol size distributions by enhancing the internally mixed/soluble accumulation mode and generating coarse mode particles. Concerning subsequent cloud formation at the second mountain, accounting for aerosol processing and regeneration increases the cloud droplet number concentration with possible implications for the ice crystal number concentration.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

PubMed

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

PubMed Central

Li, Xuejun; Xu, Jia; Yang, Yun

2015-01-01

Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts. PMID:26357510

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

Mohnen, V.A.; Aneja, V.; Bailey, B.

The report summarizes the results of the four year field measurement and data analysis program of MCCP. The MCCP is sponsored by the U.S. Environmental Protection Agency as part of the joint U.S. Forest Service-EPA Spruce-Fir Research Cooperative. The objectives of the project have been met and the result is an assessment of principal atmospheric constituents as they impact the high elevation forests of the Eastern U.S. Deposition of SO4(-2), NO3(-), H(+), and NH(4+) in cloud water represents a significant input to forest canopies with elevations greater than 1000m. Cloud water deposition can exceed wet (rain) deposition and may bemore » the dominant process for input of sulfate and nitrate compounds during the growing season in high elevation forests frequently exposed to clouds. Cloud water pH concentrations may be as much as 0.6pH units lower than pH in rain. SO(4+) and NO3(-) concentrations are also higher in cloud water than in precipitation. Ozone data reveals that significant differences exist between ozone concentrations at high elevation and low elevation sites. The primary effect of the difference is to produce higher mean ozone concentrations and longer episodes at the higher elevation sites.« less

Extraction and representation of common feature from uncertain facial expressions with cloud model.

PubMed

Wang, Shuliang; Chi, Hehua; Yuan, Hanning; Geng, Jing

2017-12-01

Human facial expressions are key ingredient to convert an individual's innate emotion in communication. However, the variation of facial expressions affects the reliable identification of human emotions. In this paper, we present a cloud model to extract facial features for representing human emotion. First, the uncertainties in facial expression are analyzed in the context of cloud model. The feature extraction and representation algorithm is established under cloud generators. With forward cloud generator, facial expression images can be re-generated as many as we like for visually representing the extracted three features, and each feature shows different roles. The effectiveness of the computing model is tested on Japanese Female Facial Expression database. Three common features are extracted from seven facial expression images. Finally, the paper is concluded and remarked.

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

NASA Technical Reports Server (NTRS)

Molthan, A. L.; Haynes, J. A.; Jedlovec, G. L.; Lapenta, W. M.

2009-01-01

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Lessons Learned while Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

NASA Astrophysics Data System (ADS)

Pilone, D.

2016-12-01

As new, high data rate missions begin collecting data, the NASA's Earth Observing System Data and Information System (EOSDIS) archive is projected to grow roughly 20x to over 300PBs by 2025. To prepare for the dramatic increase in data and enable broad scientific inquiry into larger time series and datasets, NASA has been exploring the impact of applying cloud technologies throughout EOSDIS. In this talk we will provide an overview of NASA's prototyping and lessons learned in applying cloud architectures to: Highly scalable and extensible ingest and archive of EOSDIS data Going "all-in" on cloud based application architectures including "serverless" data processing pipelines and evaluating approaches to vendor-lock in Rethinking data distribution and approaches to analysis in a cloud environment Incorporating and enforcing security controls while minimizing the barrier for research efforts to deploy to NASA compliant, operational environments. NASA's Earth Observing System (EOS) is a coordinated series of satellites for long term global observations. NASA's Earth Observing System Data and Information System (EOSDIS) is a multi-petabyte-scale archive of environmental data that supports global climate change research by providing end-to-end services from EOS instrument data collection to science data processing to full access to EOS and other earth science data. On a daily basis, the EOSDIS ingests, processes, archives and distributes over 3 terabytes of data from NASA's Earth Science missions representing over 6000 data products ranging from various types of science disciplines. EOSDIS has continually evolved to improve the discoverability, accessibility, and usability of high-impact NASA data spanning the multi-petabyte-scale archive of Earth science data products.

Impact of Low Level Clouds on radiative and turbulent surface flux in southern West Africa

NASA Astrophysics Data System (ADS)

Lohou, Fabienne; Kalthoff, Norbert; Dione, Cheikh; Lothon, Marie; Adler, Bianca; Babic, Karmen; Pedruzo-Bagazgoitia, Xabier; Vila-Guerau De Arellano, Jordi

2017-04-01

During the monsoon season in West Africa, low-level clouds form almost every night and break up between 0900 and the middle of the afternoon depending on the day. The break-up of these clouds leads to the formation of boundary-layer cumuli clouds, which can sometimes evolve into deep convection. The low-level clouds have a strong impact on the radiation and energy budget at the surface and consequently on the humidity in the boundary layer and the afternoon convection. During the DACCIWA ground campaign, which took place in June and July 2016, three supersites in Benin, Ghana, and Nigeria were instrumented to document the conditions within the lower troposphere including the cloud layers. Radiative and turbulent fluxes were measured at different places by several surface stations jointly with low-level cloud occurrence during 50 days. These datasets enable the analysis of modifications in the diurnal cycle of the radiative and turbulent surface flux induced by the formation and presence of the low-level clouds. The final objective of this study is to estimate the error made in some NWP simulations when the diurnal cycle of low-level clouds is poorly represented or not represented at all.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

Aerosol Indirect Effect on Warm Clouds over Eastern China Using Combined CALIOP and MODIS Observations

NASA Astrophysics Data System (ADS)

Guo, Jianping; Wang, Fu; Huang, Jingfeng; Li, Xiaowen

2015-04-01

Aerosol, one of key components of the climate system, is highly variable, both temporally and spatially. It often exerts great influences on the cloud-precipitation chain processes by serving as CCN/IN, altering cloud microphysics and its life cycle. Yet, the aerosol indirect effect on clouds remains largely unknown, because the initial changes in clouds due to aerosols may be enhanced or dampened by such feedback processes as modified cloud dynamics, or evaporation of the smaller droplets due to the competition for water vapor. In this study, we attempted to quantify the aerosol effects on warm cloud over eastern China, based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO and CPR/CLOUDSAT during the period 2006 to 2010. The seasonality of aerosol from ground-based PM10 is quite different from that estimated from MODIS AOD. This result is corroborated by lower level profile of aerosol occurrence frequency from CALIOP, indicating the significant role CALIOP could play in aerosol-cloud interaction. The combined use of CALIOP and CPR facilitate the process to exactly determine the (vertical) position of warm cloud relative to aerosol, out of six scenarios in terms of aerosol-cloud mixing status in terms of aerosol-cloud mixing status, which shows as follows: AO (Aerosol only), CO (Cloud only), SASC (Single aerosol-single cloud), SADC (single aerosol-double cloud), DASC (double aerosol-single cloud), and others. Results shows that about 54% of all the cases belong to mixed status, among all the collocated aerosol-cloud cases. Under mixed condition, a boomerang shape is observed, i.e., reduced cloud droplet radius (CDR) is associated with increasing aerosol at moderate aerosol pollution (AOD<0.4), becoming saturated at AOD of 0.5, followed by an increase in CDR with aerosol. In contrast, there is no such boomerang shape found for (aerosol-cloud) separated cases. We categorize dataset into warm-season and cold-season subsets to figure out how the boomerang shape varies with season. For moderate aerosol loading (AOD<0.4), the effect on the droplet size for the "Mixed" cases is greater during cold season (denoted by a large slope), as compared with that during warm season. It is likely associated with an increase in the emission of light absorbing aerosol like smoke (black carbon), mainly caused by coal-fired heating during the cold season in China. As expected, the sensitivity of CDR to AOD is much weaker for "Separated" cases, irrespective of warm or cold seasons, indicating no real aerosol indirect effect occurring in this case. In contrast, for heavy aerosol loading (AOD>0.4), an increasing CDR with AOD can be seen in "Mixed" scenario during the warm season. Conversely, a closer look at the responses of CDR during the cold season shows that CDR decreases with AOD, although the strength is not much large. Therefore, we argue that cloud droplet size decreases with aerosol loading during cold season, irrespective of moderate or heavy atmospheric pollution. Finally, we discuss the possible factors that may influence the aerosol indirect effects on warm clouds investigated here. For instance, aerosol-cloud interaction conundrum might be affected by aerosol humidification, which is the case for MODIS AOD during warm seasons. But this issue can be partly overcome by categorizing dataset into warm-season and cold-season subsets, representing different ambient humidity condition in the atmosphere. The different boomerang shapes observed during various seasons, particularly after transition zone due to droplet saturation effect, have great implications for climate forcing by aerosol in eastern China.

Coordinated Parameterization Development and Large-Eddy Simulation for Marine and Arctic Cloud-Topped Boundary Layers

NASA Technical Reports Server (NTRS)

Bretherton, Christopher S.

2002-01-01

The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.

Autonomous, Full-Time Cloud Profiling at Arm Sites with Micro Pulse Lidar

NASA Technical Reports Server (NTRS)

Spinhirne, James D.; Campbell, James R.; Hlavka, Dennis L.; Scott, V. Stanley; Flynn, Connor J.

2000-01-01

Since the early 1990's technology advances permit ground based lidar to operate full time and profile all significant aerosol and cloud structure of the atmosphere up to the limit of signal attenuation. These systems are known as Micro Pulse Lidars (MPL), as referenced by Spinhirne (1993), and were first in operation at DOE Atmospheric Radiation Measurement (ARM) sites. The objective of the ARM program is to improve the predictability of climate change, particularly as it relates to cloud-climate feedback. The fundamental application of the MPL systems is towards the detection of all significant hydrometeor layers, to the limit of signal attenuation. The heating and cooling of the atmosphere are effected by the distribution and characteristics of clouds and aerosol concentration. Aerosol and cloud retrievals in several important areas can only be adequately obtained with active remote sensing by lidar. For cloud cover, the height and related emissivity of thin clouds and the distribution of base height for all clouds are basic parameters for the surface radiation budget, and lidar is essetial for accurate measurements. The ARM MPL observing network represents the first long-term, global lidar study known within the community. MPL systems are now operational at four ARM sites. A six year data set has been obtained at the original Oklahoma site, and there are several years of observations at tropical and artic sites. Observational results include cloud base height distributions and aerosol profiles. These expanding data sets offer a significant new resource for cloud, aerosol and atmospheric radiation analysis. The nature of the data sets, data processing algorithms, derived parameters and application results are presented.

A View from the Clouds

ERIC Educational Resources Information Center

Chudnov, Daniel

2010-01-01

Cloud computing is definitely a thing now, but it's not new and it's not even novel. Back when people were first learning about the Internet in the 1990s, every diagram that one saw showing how the Internet worked had a big cloud in the middle. That cloud represented the diverse links, routers, gateways, and protocols that passed traffic around in…

Analysis of CCN activity of Remote and Combustion Aerosol over the South East Pacific during autumn 2008 and links to Sc cloud properties

NASA Astrophysics Data System (ADS)

Freitag, S.; Clarke, A. D.; Howell, S. G.; Twohy, C. H.; Snider, J. R.; Toohey, D. W.; Shank, L.; McNaughton, C. S.; Brekhovskikh, V.; Kapustin, V.

2013-12-01

The earth's most extensive Stratocumulus (Sc) deck, situated off the coast of Northern Chile and Southern Peru, strongly influences the radiation budget and climate over the South East Pacific (SEP) by enhancing solar reflection. This feature makes Sc clouds an important constituent for climate modeling, yet these clouds are poorly represented in models. A large uncertainty in understanding the variability in these low cloud fields arises from our deficit in understanding the role of aerosol. Hence, a major goal of the VOCALS (www.eol.ucar.edu/projects/vocals) campaign in 2008 was to further explore and assess interactions of natural and anthropogenic aerosol with Sc clouds in both the more polluted coastal environment and west of 80W where we encountered nearly pristine boundary layer clouds often exposed to cloud-top entrainment of pollution aerosol from the free troposphere. Extensive airborne measurements of size-resolved aerosol volatility and chemical composition collected aboard the NCAR C-130 were analyzed with an aerosol mass spectrometer (AMS) and a single particle soot photometer (SP2) to calculate aerosol hygroscopicity (κ) and predict cloud condensation nuclei (CCN) concentration for all observed air mass types above and below cloud utilizing estimated Sc cloud supersaturations deduced from cloud-processed aerosol size distribution information. The predicted CCN agree to within 10% to measured CCN. Results from this analysis are presented here and CCN variability observed along VOCALS flight tracks is discussed in conjunction with size-resolved cloud droplet information. This includes assessing the impact of aerosol perturbations on the shape of the cloud droplet size distribution parameterized in models and satellite algorithms such as cloud top effective radius retrievals. We will further discuss cloud droplet residual composition collected using a counterflow virtual impactor (CVI) and analyzed with the AMS and SP2. Size resolved variations in residual composition and its relation to CCN composition measured outside the cloud will be examined in terms of the influence of aerosol concentration, size, and chemical composition on Sc clouds.

Cloud microstructure studies

NASA Technical Reports Server (NTRS)

Blau, H. H., Jr.; Fowler, M. G.; Chang, D. T.; Ryan, R. T.

1972-01-01

Over two thousand individual cloud droplet size distributions were measured with an optical cloud particle spectrometer flown on the NASA Convair 990 aircraft. Representative droplet spectra and liquid water content, L (gm/cu m) were obtained for oceanic stratiform and cumuliform clouds. For non-precipitating clouds, values of L range from 0.1 gm/cu m to 0.5 gm/cu m; with precipitation, L is often greater than 1 gm/cu m. Measurements were also made in a newly formed contrail and in cirrus clouds.

Role of Longwave Cloud-Radiation Feedback in the Simulation of the Madden-Julian Oscillation

NASA Technical Reports Server (NTRS)

Kim, Daehyun; Ahn, Min-Seop; Kang, In-Sik; Del Genio, Anthony D.

2015-01-01

The role of the cloud-radiation interaction in the simulation of the Madden-Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). Models with a greater GEF in the strong precipitation anomaly regime (greater than 30 mm day(-1)) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud-radiation interaction is a crucial process for climate models to correctly represent the MJO.

Computing patient data in the cloud: practical and legal considerations for genetics and genomics research in Europe and internationally.

PubMed

Molnár-Gábor, Fruzsina; Lueck, Rupert; Yakneen, Sergei; Korbel, Jan O

2017-06-20

Biomedical research is becoming increasingly large-scale and international. Cloud computing enables the comprehensive integration of genomic and clinical data, and the global sharing and collaborative processing of these data within a flexibly scalable infrastructure. Clouds offer novel research opportunities in genomics, as they facilitate cohort studies to be carried out at unprecedented scale, and they enable computer processing with superior pace and throughput, allowing researchers to address questions that could not be addressed by studies using limited cohorts. A well-developed example of such research is the Pan-Cancer Analysis of Whole Genomes project, which involves the analysis of petabyte-scale genomic datasets from research centers in different locations or countries and different jurisdictions. Aside from the tremendous opportunities, there are also concerns regarding the utilization of clouds; these concerns pertain to perceived limitations in data security and protection, and the need for due consideration of the rights of patient donors and research participants. Furthermore, the increased outsourcing of information technology impedes the ability of researchers to act within the realm of existing local regulations owing to fundamental differences in the understanding of the right to data protection in various legal systems. In this Opinion article, we address the current opportunities and limitations of cloud computing and highlight the responsible use of federated and hybrid clouds that are set up between public and private partners as an adequate solution for genetics and genomics research in Europe, and under certain conditions between Europe and international partners. This approach could represent a sensible middle ground between fragmented individual solutions and a "one-size-fits-all" approach.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

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

Atmospheric Motion in Jupiter Northern Hemisphere

NASA Image and Video Library

2000-09-25

True-color (left) and false-color (right) mosaics of Jupiter's northern hemisphere between 10 and 50 degrees latitude. Jupiter's atmospheric motions are controlled by alternating eastward and westward bands of air between Jupiter's equator and polar regions. The direction and speed of these bands influences the color and texture of the clouds seen in this mosaic. The high and thin clouds are represented by light blue, deep clouds are reddish, and high and thick clouds are white. A high haze overlying a clear, deep atmosphere is represented by dark purple. This image was taken by NASA's Galileo spacecraft on April 3, 1997 at a distance of 1.4 million kilometers (.86 million miles). http://photojournal.jpl.nasa.gov/catalog/PIA03000

Stochastic behaviour of tropical convection in observations and a multicloud model

NASA Astrophysics Data System (ADS)

Peters, K.; Jakob, C.; Davies, L.; Kumar, V.; Khouider, B.; Majda, A.

2012-12-01

The feasibility of using a stochastic multicloud model (SMCM, Khouider et al. (2010)) to represent observed tropical convection over a northern Australia coastal site is investigated. In the SMCM, area fractions of three cloud types associated with tropical convection (congestus, deep convection and stratiform) are derived employing a coarse grained birth-death process which is evolved in time using a Markov chain Monte Carlo method. Here, we force the SMCM with an observed large-scale atmospheric state to assess the feasibility of applying the model's underlying design concept to simulate observed tropical convection. The observational dataset we use here represents the best estimate of the atmospheric state for a 190x190 km2 area centered over Darwin, Australia (Jakob et al., 2011). Cloud area fractions are derived from CPOL radar following Steiner et al. (1995). We use different combinations of predictors derived from the observations (e.g. CAPE, low-level CAPE, moisture convergence, mid-tropospheric relative humidity) to obtain the evolution of the cloud ensemble as simulated by the SMCM. We find that the diagnostic performance of the SMCM depends strongly on the predictor choice and that it performs remarkably well when initiation and maintenance of convection are prescribed to depend on measures related to changes in low-level moisture. This is an encouraging result on the road towards a novel convection parameterization, aimed at overcoming the difficulties of current deterministic convection parameterizations in representing the high variability in simulated tropical convection.

InSAR Deformation Time Series Processed On-Demand in the Cloud

NASA Astrophysics Data System (ADS)

Horn, W. B.; Weeden, R.; Dimarchi, H.; Arko, S. A.; Hogenson, K.

2017-12-01

During this past year, ASF has developed a cloud-based on-demand processing system known as HyP3 (http://hyp3.asf.alaska.edu/), the Hybrid Pluggable Processing Pipeline, for Synthetic Aperture Radar (SAR) data. The system makes it easy for a user who doesn't have the time or inclination to install and use complex SAR processing software to leverage SAR data in their research or operations. One such processing algorithm is generation of a deformation time series product, which is a series of images representing ground displacements over time, which can be computed using a time series of interferometric SAR (InSAR) products. The set of software tools necessary to generate this useful product are difficult to install, configure, and use. Moreover, for a long time series with many images, the processing of just the interferograms can take days. Principally built by three undergraduate students at the ASF DAAC, the deformation time series processing relies the new Amazon Batch service, which enables processing of jobs with complex interconnected dependencies in a straightforward and efficient manner. In the case of generating a deformation time series product from a stack of single-look complex SAR images, the system uses Batch to serialize the up-front processing, interferogram generation, optional tropospheric correction, and deformation time series generation. The most time consuming portion is the interferogram generation, because even for a fairly small stack of images many interferograms need to be processed. By using AWS Batch, the interferograms are all generated in parallel; the entire process completes in hours rather than days. Additionally, the individual interferograms are saved in Amazon's cloud storage, so that when new data is acquired in the stack, an updated time series product can be generated with minimal addiitonal processing. This presentation will focus on the development techniques and enabling technologies that were used in developing the time series processing in the ASF HyP3 system. Data and process flow from job submission through to order completion will be shown, highlighting the benefits of the cloud for each step.

Improving microphysics in a convective parameterization: possibilities and limitations

NASA Astrophysics Data System (ADS)

Labbouz, Laurent; Heikenfeld, Max; Stier, Philip; Morrison, Hugh; Milbrandt, Jason; Protat, Alain; Kipling, Zak

2017-04-01

The convective cloud field model (CCFM) is a convective parameterization implemented in the climate model ECHAM6.1-HAM2.2. It represents a population of clouds within each ECHAM-HAM model column, simulating up to 10 different convective cloud types with individual radius, vertical velocities and microphysical properties. Comparisons between CCFM and radar data at Darwin, Australia, show that in order to reproduce both the convective cloud top height distribution and the vertical velocity profile, the effect of aerodynamic drag on the rising parcel has to be considered, along with a reduced entrainment parameter. A new double-moment microphysics (the Predicted Particle Properties scheme, P3) has been implemented in the latest version of CCFM and is compared to the standard single-moment microphysics and the radar retrievals at Darwin. The microphysical process rates (autoconversion, accretion, deposition, freezing, …) and their response to changes in CDNC are investigated and compared to high resolution CRM WRF simulations over the Amazon region. The results shed light on the possibilities and limitations of microphysics improvements in the framework of CCFM and in convective parameterizations in general.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Vertical profiling of aerosol particles and trace gases over the central Arctic Ocean during summer

NASA Astrophysics Data System (ADS)

Kupiszewski, P.; Leck, C.; Tjernström, M.; Sjogren, S.; Sedlar, J.; Graus, M.; Müller, M.; Brooks, B.; Swietlicki, E.; Norris, S.; Hansel, A.

2013-04-01

Unique measurements of vertical size resolved aerosol particle concentrations, trace gas concentrations and meteorological data were obtained during the Arctic Summer Cloud Ocean Study (ASCOS, http://www.ascos.se), an International Polar Year project aimed at establishing the processes responsible for formation and evolution of low-level clouds over the high Arctic summer pack ice. The experiment was conducted from onboard the Swedish icebreaker Oden, and provided both ship- and helicopter-based measurements. This study focuses on the vertical helicopter profiles and onboard measurements obtained during a three-week period when Oden was anchored to a drifting ice floe, and sheds light on the characteristics of Arctic aerosol particles and their distribution throughout the lower atmosphere. Distinct differences in aerosol particle characteristics within defined atmospheric layers are identified. Near the surface (lowermost couple hundred meters), transport from the marginal ice zone (MIZ), if sufficiently short (less than ca. 2 days), condensational growth and cloud-processing develop the aerosol population. During two of the four representative periods defined in this study, such influence is shown. At altitudes above about 1 km, long-range transport occurs frequently. However, only infrequently does large-scale subsidence descend such air masses to become entrained into the mixed layer in the high Arctic, and therefore they are unlikely to directly influence low-level stratiform cloud formation. Nonetheless, long-range transport plumes can influence the radiative balance of the PBL by influencing formation and evolution of higher clouds, as well as through precipitation transport of particles downwards. New particle formation was occasionally observed, particularly in the near-surface layer. We hypothesize that the origin of these ultrafine particles can be from biological processes, both primary and secondary, within the open leads between the pack ice and/or along the MIZ. In general, local sources, in combination with upstream boundary layer transport of precursor gases from the MIZ, are suggested to constitute the origin of CCN particles and thus be of importance for the formation of interior Arctic low level clouds during summer, and subsequently, through cloud influences, on the melting and freezing of sea ice.

Microphysical processing of aerosol particles in orographic clouds

NASA Astrophysics Data System (ADS)

Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.

2015-08-01

An explicit and detailed treatment of cloud-borne particles allowing for the consideration of aerosol cycling in clouds has been implemented into COSMO-Model, the regional weather forecast and climate model of the Consortium for Small-scale Modeling (COSMO). The effects of aerosol scavenging, cloud microphysical processing and regeneration upon cloud evaporation on the aerosol population and on subsequent cloud formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic cloud. The results allowed us to identify different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase cloud, aerosol mass is incorporated into cloud droplets by activation scavenging and released back to the atmosphere upon cloud droplet evaporation. In the mixed-phase cloud, a first cycle comprises cloud droplet activation and evaporation via the Wegener-Bergeron-Findeisen (WBF) process. A second cycle includes below-cloud scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from cloud droplets to snowflakes. In the simulated mixed-phase cloud, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snowflakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. Thereby, the processes impact the total aerosol number and mass and additionally alter the shape of the aerosol size distributions by enhancing the internally mixed/soluble Aitken and accumulation mode and generating coarse-mode particles. Concerning subsequent cloud formation at the second mountain, accounting for aerosol processing and regeneration increases the cloud droplet number concentration with possible implications for the ice crystal number concentration.

Constraining the models' response of tropical low clouds to SST forcings using CALIPSO observations

NASA Astrophysics Data System (ADS)

Cesana, G.; Del Genio, A. D.; Ackerman, A. S.; Brient, F.; Fridlind, A. M.; Kelley, M.; Elsaesser, G.

2017-12-01

Low-cloud response to a warmer climate is still pointed out as being the largest source of uncertainty in the last generation of climate models. To date there is no consensus among the models on whether the tropical low cloudiness would increase or decrease in a warmer climate. In addition, it has been shown that - depending on their climate sensitivity - the models either predict deeper or shallower low clouds. Recently, several relationships between inter-model characteristics of the present-day climate and future climate changes have been highlighted. These so-called emergent constraints aim to target relevant model improvements and to constrain models' projections based on current climate observations. Here we propose to use - for the first time - 10 years of CALIPSO cloud statistics to assess the ability of the models to represent the vertical structure of tropical low clouds for abnormally warm SST. We use a simulator approach to compare observations and simulations and focus on the low-layered clouds (i.e. z < 3.2km) as well the more detailed level perspective of clouds (40 levels from 0 to 19km). Results show that in most models an increase of the SST leads to a decrease of the low-layer cloud fraction. Vertically, the clouds deepen namely by decreasing the cloud fraction in the lowest levels and increasing it around the top of the boundary-layer. This feature is coincident with an increase of the high-level cloud fraction (z > 6.5km). Although the models' spread is large, the multi-model mean captures the observed variations but with a smaller amplitude. We then employ the GISS model to investigate how changes in cloud parameterizations affect the response of low clouds to warmer SSTs on the one hand; and how they affect the variations of the model's cloud profiles with respect to environmental parameters on the other hand. Finally, we use CALIPSO observations to constrain the model by determining i) what set of parameters allows reproducing the observed relationships and ii) what are the consequences on the cloud feedbacks. These results point toward process-oriented constraints of low-cloud responses to surface warming and environmental parameters.

A cloud-evaporation parameterization for general ciculation models

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

Schlesinger, M.E.; Oh, J.H.

1993-04-01

An evaporation-zone (EZ) model for cloud evaporation is developed. In this model a cloud consists of I [open quotes]cloudlets,[close quotes] each comprising cloud droplets with radii from zero to r[sub max], the latter value depending on the drop size distribution (DSD). Evaporation occurs only within the EZ comprised of J[le]I cloudlets. When the cloudlet at cloud edge evaporates, the EZ progresses one cloudlet into the cloud's interior. This eventually results in evaporation of the cloud in time t[sub E] = K(H/h)r[sup 2][sub max](1[minus]S[sub e])[sup [minus]1] where H is the cloud thickness, h the EZ thickness, S[sub e] the environmental saturationmore » ratio, and K a constant. Values of t[sub E](1[minus]S[sub e]) versus h are presented for eight observed DSDs. For use in atmospheric general circulation models (GCMs), the cloud evaporation process is represented by dm/dt=[minus](1[minus]S[sub e])m/[tau], where m is the cloud-water mixing ratio and [tau]=K(H/h)r[sup 2][sub max]n[sup [minus]1]. With parameter n chosen sufficiently large, a GCM cloud will evaporate virtually entirely in time t[sub E], for example, 99.3% for n = 5. Values of [tau] for use in the multilayer atmospheric CRCM have been determined by performing ten perpetual-January simulations and ten perpetual-July simulations, each set of ten for prescribed pairs of [tau] values for stratiform ([tau][sub s]) and cumuloform ([tau][sub c]) clouds. An optimum choice of [tau][sub s] and [tau][sub c], based on minimizing the errors of the model's simulated cloudiness, planetary albedo, outgoing longwave radiation, and precipitation, is [tau][sub s]=[tau][sub c] = 3 min. This corresponds to t[sub E](1-S[sub e]) = 15 min for both stratiform and cumuloform clouds; hence, to an EZ thickness of about 0.6-0.8 m for stratus, stratocumulus, and altostratus clouds, 2-3 m for nimbostratus and cumulus clouds, and 17 m for cumulonimbus clouds. 18 refs., 6 figs.« less

Processing AIRS Scientific Data Through Level 2

NASA Technical Reports Server (NTRS)

Oliphant, Robert; Lee, Sung-Yung; Chahine, Moustafa; Susskind, Joel; arnet, Christopher; McMillin, Larry; Goldberg, Mitchell; Blaisdell, John; Rosenkranz, Philip; Strow, Larrabee

2007-01-01

The Atmospheric Infrared Spectrometer (AIRS) Science Processing System (SPS) is a collection of computer programs, denoted product generation executives (PGEs), for processing the readings of the AIRS suite of infrared and microwave instruments orbiting the Earth aboard NASA s Aqua spacecraft. AIRS SPS at an earlier stage of development was described in "Initial Processing of Infrared Spectral Data' (NPO-35243), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 39. To recapitulate: Starting from level 0 (representing raw AIRS data), the PGEs and their data products are denoted by alphanumeric labels (1A, 1B, and 2) that signify the successive stages of processing. The cited prior article described processing through level 1B (the level-2 PGEs were not yet operational). The level-2 PGEs, which are now operational, receive packages of level-1B geolocated radiance data products and produce such geolocated geophysical atmospheric data products such as temperature and humidity profiles. The process of computing these geophysical data products is denoted "retrieval" and is quite complex. The main steps of the process are denoted microwave-only retrieval, cloud detection and cloud clearing, regression, full retrieval, and rapid transmittance algorithm.

Hurricane Irma's Cloud Structure as Seen by NASA's AIRS

NASA Image and Video Library

2017-09-08

The large-scale structure of clouds in and around Hurricane Irma is seen in this animation and still image created with data from the Atmospheric Infrared Sounder (AIRS) instrument on NASA's Aqua satellite. The clouds are typical of tropical areas both nearby and away from tropical cyclones. Observations were taken at 1 p.m. EDT (5 p.m. UTC) on Tuesday, Sept. 5, 2017, as Irma approached the Caribbean islands and was just becoming a powerful Category 5 storm. Each cylinder represents a volume of cloud detected by AIRS. The oval cylinder ends represent a region viewed by AIRS, with the oval sizes adjusted to reflect the proportion of clouds filling the area viewed. The largest ovals are about 30 miles (45 kilometers) across. The height of the cylinders indicates the cloud thickness, with thickest clouds reaching down to the surface. The vertical scale is exaggerated 15 times. Colors represent temperatures at the tops of the clouds. The perspective views the storm diagonally from above with an initial view toward the north-northwest, with the perspective rotating clockwise for a full circle. The area depicted is about 1,000 miles by 800 miles across (1,600 by 1,300 kilometers). At the start of the loop, North America is seen at the top of the image, and coastal Venezuela at the lower right. In the initial perspective, cirrus clouds (thin and blue), associated with flow outward from the top of the hurricane, overlie warmer (pink and red) shallow clouds. About five seconds into the loop, the deep clouds in the middle of Irma are easily seen. The most dangerous parts of Irma are within the region of high and cold (blue), thick clouds surrounding the central eye. The clouds are cold because they are carried to high, cold altitudes by vigorous thunderstorms within the hurricane. The eye itself is nearly cloud free, but the few clouds within it are low and warm. As the perspective shift toward the south-southeast around seven seconds into the loop, another storm system well north of Irma can be seen. It contains high, thick clouds, with more cirrus carried outward over shallow clouds. At about nine seconds, more outflow from Irma is seen, with high, thin clouds over shallow clouds once again apparent. Shortly afterward when the view is toward the southwest, yet more deep clouds and their outflowing cirrus clouds are apparent. This image depicts many of the clouds typical of the tropics even when cyclones are not present: high, cold thunderstorms pushing cirrus clouds over nearby regions containing many warm, shallow clouds. The animation also shows the structure typical of tropical cyclones around the world: very strong thunderstorms lifting clouds into cold parts of the atmosphere, with strong outflow at upper levels carrying cirrus clouds away from the storm center, and the storm organized symmetrically around a central eye. https://photojournal.jpl.nasa.gov/catalog/PIA21950

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Integrated Modeling of Aerosol, Cloud, Precipitation and Land Processes at Satellite-Resolved Scales

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa; Tao, Wei-Kuo; Chin, Mian; Braun, Scott; Case, Jonathan; Hou, Arthur; Kumar, Anil; Kumar, Sujay; Lau, William; Matsui, Toshihisa;

Evaluating the spatio-temporal performance of sky imager based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, T.; Kalisch, J.; Lorenz, E.; Heinemann, D.

2015-10-01

Clouds are the dominant source of variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the world-wide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a shortest-term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A two month dataset with images from one sky imager and high resolutive GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series in different cloud scenarios. Overall, the sky imager based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depend strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions

NASA Astrophysics Data System (ADS)

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.; Bazile, E.; Beau, I.; Blossey, P. N.; Boutle, I. A.; de Bruijn, C.; Cheng, A.; van der Dussen, J.; Fletcher, J.; Dal Gesso, S.; Jam, A.; Kawai, H.; Cheedela, S. K.; Larson, V. E.; Lefebvre, M.-P.; Lock, A. P.; Meyer, N. R.; de Roode, S. R.; de Rooy, W.; Sandu, I.; Xiao, H.; Xu, K.-M.

2017-10-01

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

Intelligent cloud computing security using genetic algorithm as a computational tools

NASA Astrophysics Data System (ADS)

Razuky AL-Shaikhly, Mazin H.

2018-05-01

An essential change had occurred in the field of Information Technology which represented with cloud computing, cloud giving virtual assets by means of web yet awesome difficulties in the field of information security and security assurance. Currently main problem with cloud computing is how to improve privacy and security for cloud “cloud is critical security”. This paper attempts to solve cloud security by using intelligent system with genetic algorithm as wall to provide cloud data secure, all services provided by cloud must detect who receive and register it to create list of users (trusted or un-trusted) depend on behavior. The execution of present proposal has shown great outcome.

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

NASA Technical Reports Server (NTRS)

Krueger, Steven K.

1998-01-01

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

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

NASA Astrophysics Data System (ADS)

Gézero, L.; Antunes, C.

2017-05-01

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

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

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

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.

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

An All Sky Instantaneous Shortwave Solar Radiation Model for Mountainous Terrain

NASA Astrophysics Data System (ADS)

Zhang, S.; Li, X.; She, J.

2017-12-01

In mountainous terrain, solar radiation shows high heterogeneity in space and time because of strong terrain shading effects and significant variability of cloud cover. While existing GIS-based solar radiation models simulate terrain shading effects with relatively high accuracy and models based on satellite datasets consider fine scale cloud attenuation processes, none of these models have considered the geometrical relationships between sun, cloud, and terrain, which are important over mountainous terrain. In this research we propose sky cloud maps to represent cloud distribution in a hemispherical sky using MODIS cloud products. By overlaying skyshed (visible area in the hemispherical sky derived from DEM), sky map, and sky cloud maps, we are able to consider both terrain shading effects and anisotropic cloud attenuation in modeling instantaneous direct and diffuse solar radiation in mountainous terrain. The model is evaluated with field observations from three automatic weather stations in the Tizinafu watershed in the Kunlun Mountains of northwestern China. Overall, under all sky conditions, the model overestimates instantaneous global solar radiation with a mean absolute relative difference (MARD) of 22%. The model is also evaluated under clear sky (clearness index of more than 0.75) and partly cloudy sky (clearness index between 0.35 and 0.75) conditions with MARDs of 5.98% and 23.65% respectively. The MARD for very cloudy sky (clearness index less than 0.35) is relatively high. But these days occur less than 1% of the time. The model is sensitive to DEM data error, algorithms used in delineating skyshed, and errors in MODIS atmosphere and cloud products. Our model provides a novel approach for solar radiation modeling in mountainous areas.

Comparative exoplanetology with consistent retrieval methods

NASA Astrophysics Data System (ADS)

Barstow, Joanna Katy; Aigrain, Suzanne; Irwin, Patrick Gerard Joseph; Sing, David

2016-10-01

The number of hot Jupiters with broad wavelength spectroscopic data has finally become large enough to make comparative planetology a reasonable proposition. New results presented by Sing et al. (2016) showcase ten hot Jupiters with spectra from the Hubble Space Telescope and photometry from Spitzer, providing insights into the presence of clouds and hazes.Spectral retrieval methods allow interpretation of exoplanet spectra using simple models, with minimal prior assumptions. This is particularly useful for exotic exoplanets, for which we may not yet fully understand the physical processes responsible for their atmospheric characteristics. Consistent spectral retrieval of a range of exoplanets can allow robust comparisons of their derived atmospheric properties.I will present a retrieval analysis using the NEMESIS code (Irwin et al. 2008) of the ten hot Jupiter spectra presented by Sing et al. (2016). The only distinctive aspects of the model for each planet are the mass and radius, and the temperature range explored. All other a priori model parameters are common to all ten objects. We test a range of cloud and haze scenarios, which include: Rayleigh-dominated and grey clouds; different cloud top pressures; and both vertically extended and vertically confined clouds.All ten planets, with the exception of WASP-39b, can be well represented by models with at least some haze or cloud. Our analysis of cloud properties has uncovered trends in cloud top pressure, vertical extent and particle size with planet equilibrium temperature. Taken together, we suggest that these trends indicate condensation and sedimentation of at least two different cloud species across planets of different temperatures, with condensates forming higher up in hotter atmospheres and moving progressively further down in cooler planets.Sing, D. et al. (2016), Nature, 529, 59Irwin, P. G. J. et al. (2008), JQSRT, 109, 1136

Simulation of Asia Dust and Cloud Interaction Over Pacific Ocean During Pacdex

NASA Astrophysics Data System (ADS)

Long, X.; Huang, J.; Cheng, C.; Wang, W.

2007-12-01

The effect of dust plume on the Pacific cloud systems and the associated radiative forcing is an outstanding problem for understanding climate change. Many studies showing that dust aerosol might be a good absorber for solar radiation, at the same time dust aerosols could affect the cloud's formation and precipitation by its capability as cloud condensation nuclei (CCN) and ice forming nuclei (IFN). But the role of aerosols in clouds and precipitation is very complex. Simulation of interaction between cloud and dust aerosols requires recognition that the aerosol cloud system comprises coupled components of dynamics, aerosol and cloud microphysics, radiation processes. In this study, we investigated the interaction between dust aerosols and cloud with WRF which coupled with detailed cloud microphysics processes and dust process. The observed data of SACOL (Semi-Arid Climate and Environment Observatory of Lanzhou University) and PACDEX (Pacific Dust Experiment) is used as the initialization which include the vertical distributions and concentration of dust particles. Our results show that dust aerosol not only impacts cloud microphysical processes but also cloud microstructure; Dust aerosols can act as effective ice nuclei and intensify the ice-forming processes.

A modeling analysis program for the JPL Table Mountain Io sodium cloud data

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Goldberg, B. A.

1986-01-01

Progress and achievements in the second year are discussed in three main areas: (1) data quality review of the 1981 Region B/C images; (2) data processing activities; and (3) modeling activities. The data quality review revealed that almost all 1981 Region B/C images are of sufficient quality to be valuable in the analyses of the JPL data set. In the second area, the major milestone reached was the successful development and application of complex image-processing software required to render the original image data suitable for modeling analysis studies. In the third area, the lifetime description of sodium atoms in the planet magnetosphere was improved in the model to include the offset dipole nature of the magnetic field as well as an east-west electric field. These improvements are important in properly representing the basic morphology as well as the east-west asymmetries of the sodium cloud.

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

NASA Astrophysics Data System (ADS)

Nag, B.

2016-12-01

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

Characterization of ice nucleating particles during continuous springtime measurements in Prudhoe Bay: an Arctic oilfield location

NASA Astrophysics Data System (ADS)

Creamean, J.; Spada, N. J.; Kirpes, R.; Pratt, K.

2017-12-01

Aerosols that serve as ice nucleating particles (INPs) have the potential to modulate cloud microphysical properties. INPs can thus subsequently impact cloud radiative forcing in addition to modification of precipitation formation processes. In regions such as the Arctic, aerosol-cloud interactions are severely understudied yet have significant implications for surface radiation reaching the sea ice and snow surfaces. Further, uncertainties in model representations of heterogeneous ice nucleation are a significant hindrance to simulating Arctic mixed-phase cloud processes. Characterizing a combination of aerosol chemical, physical, and ice nucleating properties is pertinent to evaluating of the role of aerosols in altering Arctic cloud microphysics. We present preliminary results from an aerosol sampling campaign called INPOP (Ice Nucleating Particles at Oliktok Point), which took place at a U.S. Department of Energy's Atmospheric Radiation Measurement (DOE ARM) facility on the North Slope of Alaska. Three time- and size-resolved aerosol samplers were deployed from 1 Mar to 31 May 2017 and were co-located with routine measurements of aerosol number, size, chemical, and radiative property measurements conducted by DOE ARM at their Aerosol Observing System (AOS). Offline analysis of samples collected at a daily time resolution included composition and morphology via single-particle analysis and drop freezing measurements for INP concentrations, while analysis of 12-hourly samples included mass, optical, and elemental composition. We deliberate the possible influences on the aerosol and INP population from the Prudhoe Bay oilfield resource extraction and daily operations in addition to what may be local background or long-range transported aerosol. To our knowledge our results represent some of the first INP characterization measurements in an Arctic oilfield location and can be used as a benchmark for future INP characterization studies in Arctic locations impacted by local resource extraction pollution. Ultimately, these results can be used to evaluate the impacts of oil exploration activities on Arctic cloud aerosol composition and possible linkages to Arctic cloud ice formation.

Applications and Improvement of a Coupled, Global and Cloud-Resolving Modeling System

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Chern, J.; Atlas, R.

2005-01-01

Recently Grabowski (2001) and Khairoutdinov and Randall (2001) have proposed the use of 2D CFWs as a "super parameterization" [or multi-scale modeling framework (MMF)] to represent cloud processes within atmospheric general circulation models (GCMs). In the MMF, a fine-resolution 2D CRM takes the place of the single-column parameterization used in conventional GCMs. A prototype Goddard MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM) is now being developed. The prototype includes the fvGCM run at 2.50 x 20 horizontal resolution with 32 vertical layers from the surface to 1 mb and the 2D (x-z) GCE using 64 horizontal and 32 vertical grid points with 4 km horizontal resolution and a cyclic lateral boundary. The time step for the 2D GCE would be 15 seconds, and the fvGCM-GCE coupling frequency would be 30 minutes (i.e. the fvGCM physical time step). We have successfully developed an fvGCM-GCE coupler for this prototype. Because the vertical coordinate of the fvGCM (a terrain-following floating Lagrangian coordinate) is different from that of the GCE (a z coordinate), vertical interpolations between the two coordinates are needed in the coupler. In interpolating fields from the GCE to fvGCM, we use an existing fvGCM finite- volume piecewise parabolic mapping (PPM) algorithm, which conserves the mass, momentum, and total energy. A new finite-volume PPM algorithm, which conserves the mass, momentum and moist static energy in the z coordinate, is being developed for interpolating fields from the fvGCM to the GCE. In the meeting, we will discuss the major differences between the two MMFs (i.e., the CSU MMF and the Goddard MMF). We will also present performance and critical issues related to the MMFs. In addition, we will present multi-dimensional cloud datasets (i.e., a cloud data library) generated by the Goddard MMF that will be provided to the global modeling community to help improve the representation and performance of moist processes in climate models and to improve our understanding of cloud processes globally (the software tools needed to produce cloud statistics and to identify various types of clouds and cloud systems from both high-resolution satellite and model data will be also presented).

Potential New Lidar Observations for Cloud Studies

NASA Technical Reports Server (NTRS)

Winker, Dave; Hu, Yong; Narir, Amin; Cai, Xia

2015-01-01

The response of clouds to global warming represents a major uncertainty in estimating climate sensitivity. These uncertainties have been tracked to shallow marine clouds in the tropics and subtropics. CALIOP observations have already been used extensively to evaluate model predictions of shallow cloud fraction and top height (Leahy et al. 2013; Nam et al 2012). Tools are needed to probe the lowest levels of the troposphere. The large footprint of satellite lidars gives large multiple scattering from clouds which presents new possibilities for cloud retrievals to constrain model predictions.

SparkClouds: visualizing trends in tag clouds.

PubMed

Lee, Bongshin; Riche, Nathalie Henry; Karlson, Amy K; Carpendale, Sheelash

2010-01-01

Tag clouds have proliferated over the web over the last decade. They provide a visual summary of a collection of texts by visually depicting the tag frequency by font size. In use, tag clouds can evolve as the associated data source changes over time. Interesting discussions around tag clouds often include a series of tag clouds and consider how they evolve over time. However, since tag clouds do not explicitly represent trends or support comparisons, the cognitive demands placed on the person for perceiving trends in multiple tag clouds are high. In this paper, we introduce SparkClouds, which integrate sparklines into a tag cloud to convey trends between multiple tag clouds. We present results from a controlled study that compares SparkClouds with two traditional trend visualizations—multiple line graphs and stacked bar charts—as well as Parallel Tag Clouds. Results show that SparkClouds ability to show trends compares favourably to the alternative visualizations.

Proposal for a Security Management in Cloud Computing for Health Care

PubMed Central

Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources. PMID:24701137

Proposal for a security management in cloud computing for health care.

PubMed

Haufe, Knut; Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources.

Polar clouds and radiation in satellite observations, reanalyses, and climate models

NASA Astrophysics Data System (ADS)

Lenaerts, Jan T. M.; Van Tricht, Kristof; Lhermitte, Stef; L'Ecuyer, Tristan S.

2017-04-01

Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007-2010) to evaluate simulated clouds and radiation over both polar ice sheets and oceans in state-of-the-art atmospheric reanalyses (ERA-Interim and Modern Era Retrospective-Analysis for Research and Applications-2) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model ensemble. First, we show that, compared to Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled, CloudSat-CALIPSO better represents cloud liquid and ice water path over high latitudes, owing to its recent explicit determination of cloud phase that will be part of its new R05 release. The reanalyses and climate models disagree widely on the amount of cloud liquid and ice in the polar regions. Compared to the observations, we find significant but inconsistent biases in the model simulations of cloud liquid and ice water, as well as in the downwelling radiation components. The CMIP5 models display a wide range of cloud characteristics of the polar regions, especially with regard to cloud liquid water, limiting the representativeness of the multimodel mean. A few CMIP5 models (CNRM, GISS, GFDL, and IPSL_CM5b) clearly outperform the others, which enhances credibility in their projected future cloud and radiation changes over high latitudes. Given the rapid changes in polar regions and global feedbacks involved, future climate model developments should target improved representation of polar clouds. To that end, remote sensing observations are crucial, in spite of large remaining observational uncertainties, which is evidenced by the substantial differences between the two data sets.

Observations and Modeling of the Green Ocean Amazon 2014/15. CHUVA Field Campaign Report

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

Machado, L. A. T.

2016-03-01

The physical processes inside clouds are one of the most unknown components of weather and climate systems. A description of cloud processes through the use of standard meteorological parameters in numerical models has to be strongly improved to accurately describe the characteristics of hydrometeors, latent heating profiles, radiative balance, air entrainment, and cloud updrafts and downdrafts. Numerical models have been improved to run at higher spatial resolutions where it is necessary to explicitly describe these cloud processes. For instance, to analyze the effects of global warming in a given region it is necessary to perform simulations taking into account allmore » of the cloud processes described above. Another important application that requires this knowledge is satellite precipitation estimation. The analysis will be performed focusing on the microphysical evolution and cloud life cycle, different precipitation estimation algorithms, the development of thunderstorms and lightning formation, processes in the boundary layer, and cloud microphysical modeling. This project intends to extend the knowledge of these cloud processes to reduce the uncertainties in precipitation estimation, mainly from warm clouds, and, consequently, improve knowledge of the water and energy budget and cloud microphysics.« less

Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

PubMed Central

Kudtarkar, Parul; DeLuca, Todd F.; Fusaro, Vincent A.; Tonellato, Peter J.; Wall, Dennis P.

2010-01-01

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon’s Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon’s computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure. PMID:21258651

Global and regional modeling of clouds and aerosols in the marine boundary layer during VOCALS: the VOCA intercomparison

DOE PAGES

Wyant, M. C.; Bretherton, Christopher S.; Wood, Robert; ...

2015-01-09

A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar tomore » observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO 2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.« less

Efficient Open Source Lidar for Desktop Users

NASA Astrophysics Data System (ADS)

Flanagan, Jacob P.

Lidar --- Light Detection and Ranging --- is a remote sensing technology that utilizes a device similar to a rangefinder to determine a distance to a target. A laser pulse is shot at an object and the time it takes for the pulse to return in measured. The distance to the object is easily calculated using the speed property of light. For lidar, this laser is moved (primarily in a rotational movement usually accompanied by a translational movement) and records the distances to objects several thousands of times per second. From this, a 3 dimensional structure can be procured in the form of a point cloud. A point cloud is a collection of 3 dimensional points with at least an x, a y and a z attribute. These 3 attributes represent the position of a single point in 3 dimensional space. Other attributes can be associated with the points that include properties such as the intensity of the return pulse, the color of the target or even the time the point was recorded. Another very useful, post processed attribute is point classification where a point is associated with the type of object the point represents (i.e. ground.). Lidar has gained popularity and advancements in the technology has made its collection easier and cheaper creating larger and denser datasets. The need to handle this data in a more efficiently manner has become a necessity; The processing, visualizing or even simply loading lidar can be computationally intensive due to its very large size. Standard remote sensing and geographical information systems (GIS) software (ENVI, ArcGIS, etc.) was not originally built for optimized point cloud processing and its implementation is an afterthought and therefore inefficient. Newer, more optimized software for point cloud processing (QTModeler, TopoDOT, etc.) usually lack more advanced processing tools, requires higher end computers and are very costly. Existing open source lidar approaches the loading and processing of lidar in an iterative fashion that requires implementing batch coding and processing time that could take months for a standard lidar dataset. This project attempts to build a software with the best approach for creating, importing and exporting, manipulating and processing lidar, especially in the environmental field. Development of this software is described in 3 sections - (1) explanation of the search methods for efficiently extracting the "area of interest" (AOI) data from disk (file space), (2) using file space (for storage), budgeting memory space (for efficient processing) and moving between the two, and (3) method development for creating lidar products (usually raster based) used in environmental modeling and analysis (i.e.: hydrology feature extraction, geomorphological studies, ecology modeling, etc.).

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

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

Mechem, David B.; de Szoeke, Simon P.; Yuter, Sandra E.

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

A Multi-Model Analysis of the Cloud Phase Transition in 16 GCMs Using Satellite Observations (CALIPSO/GPCP) and Reanalysis Data (ECMWF/MERRA).

NASA Astrophysics Data System (ADS)

Cesana, G.; Waliser, D. E.; Jiang, X.; Li, J. L. F.

2014-12-01

The ubiquitous presence of clouds within the troposphere contributes to modulate the radiative balance of the earth-atmosphere system. Depending on their cloud phase, clouds may have different microphysical and macrophysical properties, and hence, different radiative effects. In this study, we took advantage of climate runs from the GASS-YoTC and AMIP multi-model experiments to document the differences associated to the cloud phase parameterizations of 16 GCMs. A particular emphasize has been put on the vertical structure of the transition between liquid and ice in clouds. A way to intercompare the models regardless of their cloud fraction is to study the ratio of the ice mass to the total mass of the condensed water. To address the challenge of evaluating the modeled cloud phase, we profited from the cloud phase climatology so called CALIPSO-GOCCP, which separates liquid clouds from ice clouds at global scale, with a high vertical resolution (480m), above all surfaces. We also used reanalysis data and GPCP satellite observations to investigate the influence of the temperature, the relative humidity, the vertical wind speed and the precipitations on the cloud phase transition. In 12 (of 16) models, there are too few super cooled liquid in clouds compared to observations, mostly in the high troposphere. We exhibited evidences of the link between the cloud phase transition and the humidity, the vertical wind speed as well as the precipitations. Some cloud phase schemes are more affected by the humidity and the vertical velocity and some other by the precipitations. Although a few models can reproduce the observe relation between cloud phase and temperature, humidity, vertical velocity or precipitations, none of them perform well for all the parameters. An important result of this study is that the T-dependent phase parameterizations do not allow simulating the complexity of the observed cloud phase transition. Unfortunately, more complex microphysics schemes do not succeed to reproduce all the processes neither. Finally, thanks to the combined use of CALIPSO-GOCCP and ECMWF water vapor pressure, we showed an updated version of the Clausius-Clapeyron water vapor phase diagram. This diagram represents a new tool to improve the simulation of the cloud phase transition in climate models.

Cloud computing geospatial application for water resources based on free and open source software and open standards - a prototype

NASA Astrophysics Data System (ADS)

Delipetrev, Blagoj

2016-04-01

Presently, most of the existing software is desktop-based, designed to work on a single computer, which represents a major limitation in many ways, starting from limited computer processing, storage power, accessibility, availability, etc. The only feasible solution lies in the web and cloud. This abstract presents research and development of a cloud computing geospatial application for water resources based on free and open source software and open standards using hybrid deployment model of public - private cloud, running on two separate virtual machines (VMs). The first one (VM1) is running on Amazon web services (AWS) and the second one (VM2) is running on a Xen cloud platform. The presented cloud application is developed using free and open source software, open standards and prototype code. The cloud application presents a framework how to develop specialized cloud geospatial application that needs only a web browser to be used. This cloud application is the ultimate collaboration geospatial platform because multiple users across the globe with internet connection and browser can jointly model geospatial objects, enter attribute data and information, execute algorithms, and visualize results. The presented cloud application is: available all the time, accessible from everywhere, it is scalable, works in a distributed computer environment, it creates a real-time multiuser collaboration platform, the programing languages code and components are interoperable, and it is flexible in including additional components. The cloud geospatial application is implemented as a specialized water resources application with three web services for 1) data infrastructure (DI), 2) support for water resources modelling (WRM), 3) user management. The web services are running on two VMs that are communicating over the internet providing services to users. The application was tested on the Zletovica river basin case study with concurrent multiple users. The application is a state-of-the-art cloud geospatial collaboration platform. The presented solution is a prototype and can be used as a foundation for developing of any specialized cloud geospatial applications. Further research will be focused on distributing the cloud application on additional VMs, testing the scalability and availability of services.

An Overview of Cloud Implementation in the Manufacturing Process Life Cycle

NASA Astrophysics Data System (ADS)

Kassim, Noordiana; Yusof, Yusri; Hakim Mohamad, Mahmod Abd; Omar, Abdul Halim; Roslan, Rosfuzah; Aryanie Bahrudin, Ida; Ali, Mohd Hatta Mohamed

2017-08-01

The advancement of information and communication technology (ICT) has changed the structure and functions of various sectors and it has also started to play a significant role in modern manufacturing in terms of computerized machining and cloud manufacturing. It is important for industries to keep up with the current trend of ICT for them to be able survive and be competitive. Cloud manufacturing is an approach that wanted to realize a real-world manufacturing processes that will apply the basic concept from the field of Cloud computing to the manufacturing domain called Cloud-based manufacturing (CBM) or cloud manufacturing (CM). Cloud manufacturing has been recognized as a new paradigm for manufacturing businesses. In cloud manufacturing, manufacturing companies need to support flexible and scalable business processes in the shop floor as well as the software itself. This paper provides an insight or overview on the implementation of cloud manufacturing in the modern manufacturing processes and at the same times analyses the requirements needed regarding process enactment for Cloud manufacturing and at the same time proposing a STEP-NC concept that can function as a tool to support the cloud manufacturing concept.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

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

USGS Publications Warehouse

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

2017-01-01

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

What's Old is New in the Large Magellanic Cloud

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Poster Version Large Magellanic Cloud

This vibrant image from NASA's Spitzer Space Telescope shows the Large Magellanic Cloud, a satellite galaxy to our own Milky Way galaxy.

The infrared image, a mosaic of 300,000 individual tiles, offers astronomers a unique chance to study the lifecycle of stars and dust in a single galaxy. Nearly one million objects are revealed for the first time in this Spitzer view, which represents about a 1,000-fold improvement in sensitivity over previous space-based missions. Most of the new objects are dusty stars of various ages populating the Large Magellanic Cloud; the rest are thought to be background galaxies.

The blue color in the picture, seen most prominently in the central bar, represents starlight from older stars. The chaotic, bright regions outside this bar are filled with hot, massive stars buried in thick blankets of dust. The red color around these bright regions is from dust heated by stars, while the red dots scattered throughout the picture are either dusty, old stars or more distant galaxies. The greenish clouds contain cooler interstellar gas and molecular-sized dust grains illuminated by ambient starlight.

Astronomers say this image allows them to quantify the process by which space dust -- the same stuff that makes up planets and even people -- is recycled in a galaxy. The picture shows dust at its three main cosmic hangouts: around the young stars, where it is being consumed (red-tinted, bright clouds); scattered about in the space between stars (greenish clouds); and in expelled shells of material from old stars (randomly-spaced red dots).

The Large Magellanic Cloud, located 160,000 light-years from Earth, is one of a handful of dwarf galaxies that orbit our own Milky Way. It is approximately one-third as wide as the Milky Way, and, if it could be seen in its entirety, would cover the same amount of sky as a grid of about 480 full moons. About one-third of the entire galaxy can be seen in the Spitzer image.

This picture is a composite of infrared light captured by Spitzer. Light with wavelengths of 3.6 (blue) and 8 (green) microns was captured by the telescope's infrared array camera; 24-micron light (red) was detected by the multiband imaging photometer.

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Demek, Scott R.

2010-01-01

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Interactive coupling of regional climate and sulfate aerosol models over eastern Asia

NASA Astrophysics Data System (ADS)

Qian, Yun; Giorgi, Filippo

1999-03-01

The NCAR regional climate model (RegCM) is interactively coupled to a simple radiatively active sulfate aerosol model over eastern Asia. Both direct and indirect aerosol effects are represented. The coupled model system is tested for two simulation periods, November 1994 and July 1995, with aerosol sources representative of present-day anthropogenic sulfur emissions. The model sensitivity to the intensity of the aerosol source is also studied. The main conclusions from our work are as follows: (1) The aerosol distribution and cycling processes show substantial regional spatial variability, and temporal variability varying on a range of scales, from the diurnal scale of boundary layer and cumulus cloud evolution to the 3-10 day scale of synoptic scale events and the interseasonal scale of general circulation features; (2) both direct and indirect aerosol forcings have regional effects on surface climate; (3) the regional climate response to the aerosol forcing is highly nonlinear, especially during the summer, due to the interactions with cloud and precipitation processes; (4) in our simulations the role of the aerosol indirect effects is dominant over that of direct effects; (5) aerosol-induced feedback processes can affect the aerosol burdens at the subregional scale. This work constitutes the first step in a long term research project aimed at coupling a hierarchy of chemistry/aerosol models to the RegCM over the eastern Asia region.

FUNCTION GENERATOR FOR ANALOGUE COMPUTERS

DOEpatents

Skramstad, H.K.; Wright, J.H.; Taback, L.

1961-12-12

An improved analogue computer is designed which can be used to determine the final ground position of radioactive fallout particles in an atomic cloud. The computer determines the fallout pattern on the basis of known wind velocity and direction at various altitudes, and intensity of radioactivity in the mushroom cloud as a function of particle size and initial height in the cloud. The output is then displayed on a cathode-ray tube so that the average or total luminance of the tube screen at any point represents the intensity of radioactive fallout at the geographical location represented by that point. (AEC)

Why do we have such difficulty assessing aerosol impacts in Southeast Asia? Examining the representativeness of regional in situ, remote sensing, and modeling data using examples from a recent field trial

NASA Astrophysics Data System (ADS)

Reid, J.; Hyer, E. J.; Lagrosas, N.; Salinas Cortijo, S. V.; Campbell, J. R.; Chew, B.; Cook, J.; Di Girolamo, L.; Kuciauskas, A. P.; Johnson, R. S.; Jonsson, H.; Lynch, P.; Sessions, W.; Simpas, J. B.; Turk, F. J.; Wang, J.

2012-12-01

Southeast Asia faces numerous climate change issues, and the interaction between aerosol particles, clouds, and precipitation is thought to impact the environment in this region at both weather and climate scales. Aerosol particles have direct radiative effects, indirect effects through interaction with clouds and precipitation, and also act as a tracer for other processes affecting the carbon cycle or atmospheric chemistry. Southeast Asia also hosts some of the most complex meteorological phenomenon of the world, challenging in situ, remote sensing and modeling systems. Indeed, there is more diversity in satellite based aerosol, fire, cloud, and precipitation products in Southeast Asia than perhaps anywhere else in the world outside of the poles. In addition to serious direct challenges to aerosol observability in Southeast Asia, such as persistent ubiquitous cloud cover, there are also contextual biases (such as for aerosol retrievals the classic clear sky bias). Contextual bias affects the representativeness of nearly all aerosol assessments in Southeast Asia. As part of the 7 Southeast Asian Studies (7SEAS) program, a small intensive study was conducted in Singapore and the Palawan Archipelago in September 2011 to study the flow of biomass burning smoke through the South China/East Sea and into the summertime monsoonal trough. Analysis of field data coupled with multiple satellite and model products allowed us to investigate questions on the representativeness of data and to what extent they capture the 'true' state of the meteorological and aerosol environment. Four specific representativeness issues are presented based on IOP examples: 1) Individual biases in retrievals or model simulations; 2) Sampling biases at short time scales based on product coverage; 3) Temporal and spatial scale biases inherent in large and point based measurements; 4) Contextual biases that develop from the aggregation of data products. Considering all four of these issues we conclude with a discussion of strategies for hypothesis testing and the development of regional state vectors with realistic uncertainties.

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

NASA Technical Reports Server (NTRS)

Wang, Shouping; Wang, Qing

1994-01-01

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

Cloud Processed CCN Suppress Stratus Cloud Drizzle

NASA Astrophysics Data System (ADS)

Hudson, J. G.; Noble, S. R., Jr.

2017-12-01

Conversion of sulfur dioxide to sulfate within cloud droplets increases the sizes and decreases the critical supersaturation, Sc, of cloud residual particles that had nucleated the droplets. Since other particles remain at the same sizes and Sc a size and Sc gap is often observed. Hudson et al. (2015) showed higher cloud droplet concentrations (Nc) in stratus clouds associated with bimodal high-resolution CCN spectra from the DRI CCN spectrometer compared to clouds associated with unimodal CCN spectra (not cloud processed). Here we show that CCN spectral shape (bimodal or unimodal) affects all aspects of stratus cloud microphysics and drizzle. Panel A shows mean differential cloud droplet spectra that have been divided according to traditional slopes, k, of the 131 measured CCN spectra in the Marine Stratus/Stratocumulus Experiment (MASE) off the Central California coast. K is generally high within the supersaturation, S, range of stratus clouds (< 0.5%). Because cloud processing decreases Sc of some particles, it reduces k. Panel A shows higher concentrations of small cloud droplets apparently grown on lower k CCN than clouds grown on higher k CCN. At small droplet sizes the concentrations follow the k order of the legend, black, red, green, blue (lowest to highest k). Above 13 µm diameter the lines cross and the hierarchy reverses so that blue (highest k) has the highest concentrations followed by green, red and black (lowest k). This reversed hierarchy continues into the drizzle size range (panel B) where the most drizzle drops, Nd, are in clouds grown on the least cloud-processed CCN (blue), while clouds grown on the most processed CCN (black) have the lowest Nd. Suppression of stratus cloud drizzle by cloud processing is an additional 2nd indirect aerosol effect (IAE) that along with the enhancement of 1st IAE by higher Nc (panel A) are above and beyond original IAE. However, further similar analysis is needed in other cloud regimes to determine if MASE was typical. Hudson, J.G., S. Noble, and S. Tabor, 2015: J. Geophys. Res., Atmos., 120, 3436-3452, doi:10.1002/2014JD022669.

Impact of Aerosol Processing on Orographic Clouds

NASA Astrophysics Data System (ADS)

Pousse-Nottelmann, Sara; Zubler, Elias M.; Lohmann, Ulrike

2010-05-01

Aerosol particles undergo significant modifications during their residence time in the atmosphere. Physical processes like coagulation, coating and water uptake, and aqueous surface chemistry alter the aerosol size distribution and composition. At this, clouds play a primary role as physical and chemical processing inside cloud droplets contributes considerably to the changes in aerosol particles. A previous study estimates that on global average atmospheric particles are cycled three times through a cloud before being removed from the atmosphere [1]. An explicit and detailed treatment of cloud-borne particles has been implemented in the regional weather forecast and climate model COSMO-CLM. The employed model version includes a two-moment cloud microphysical scheme [2] that has been coupled to the aerosol microphysical scheme M7 [3] as described by Muhlbauer and Lohmann, 2008 [4]. So far, the formation, transfer and removal of cloud-borne aerosol number and mass were not considered in the model. Following the parameterization for cloud-borne particles developed by Hoose et al., 2008 [5], distinction between in-droplet and in-crystal particles is made to more physically account for processes in mixed-phase clouds, such as the Wegener-Bergeron-Findeisen process and contact and immersion freezing. In our model, this approach has been extended to allow for aerosol particles in five different hydrometeors: cloud droplets, rain drops, ice crystals, snow flakes and graupel. We account for nucleation scavenging, freezing and melting processes, autoconversion, accretion, aggregation, riming and selfcollection, collisions between interstitial aerosol particles and hydrometeors, ice multiplication, sedimentation, evaporation and sublimation. The new scheme allows an evaluation of the cloud cycling of aerosol particles by tracking the particles even when scavenged into hydrometeors. Global simulations of aerosol processing in clouds have recently been conducted by Hoose et al. [6]. Our investigation regarding the influence of aerosol processing will focus on the regional scale using a cloud-system resolving model with a much higher resolution. Emphasis will be placed on orographic mixed-phase precipitation. Different two-dimensional simulations of idealized orographic clouds will be conducted to estimate the effect of aerosol processing on orographic cloud formation and precipitation. Here, cloud lifetime, location and extent as well as the cloud type will be of particular interest. In a supplementary study, the new parameterization will be compared to observations of total and interstitial aerosol concentrations and size distribution at the remote high alpine research station Jungfraujoch in Switzerland. In addition, our simulations will be compared to recent simulations of aerosol processing in warm, mixed-phase and cold clouds, which have been carried out at the location of Jungfraujoch station [5]. References: [1] Pruppacher & Jaenicke (1995), The processing of water vapor and aerosols by atmospheric clouds, a global estimate, Atmos. Res., 38, 283295. [2] Seifert & Beheng (2006), A two-moment microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 4566. [3] Vignati et al. (2004), An efficient size-resolved aerosol microphysics module for large-scale transport models, J. Geophys. Res., 109, D22202 [4] Muhlbauer & Lohmann (2008), Sensitivity studies of the role of aerosols in warm-phase orographic precipitation in different flow regimes, J. Atmos. Sci., 65, 25222542. [5] Hoose et al. (2008), Aerosol processing in mixed-phase clouds in ECHAM5HAM: Model description and comparison to observations, J. Geophys. Res., 113, D071210. [6] Hoose et al. (2008), Global simulations of aerosol processing in clouds, Atmos. Chem. Phys., 8, 69396963.

Open-cell and closed-cell clouds off Peru [detail

NASA Image and Video Library

2017-12-08

2010/107 - 04/17 at 21 :05 UTC. Open-cell and closed-cell clouds off Peru, Pacific Ocean. To view the full fame of this image to go: www.flickr.com/photos/gsfc/4557497219/ Resembling a frosted window on a cold winter's day, this lacy pattern of marine clouds was captured off the coast of Peru in the Pacific Ocean by the MODIS on the Aqua satellite on April 19, 2010. The image reveals both open- and closed-cell cumulus cloud patterns. These cells, or parcels of air, often occur in roughly hexagonal arrays in a layer of fluid (the atmosphere often behaves like a fluid) that begins to "boil," or convect, due to heating at the base or cooling at the top of the layer. In "closed" cells warm air is rising in the center, and sinking around the edges, so clouds appear in cell centers, but evaporate around cell edges. This produces cloud formations like those that dominate the lower left. The reverse flow can also occur: air can sink in the center of the cell and rise at the edge. This process is called "open cell" convection, and clouds form at cell edges around open centers, which creates a lacy, hollow-looking pattern like the clouds in the upper right. Closed and open cell convection represent two stable atmospheric configurations — two sides of the convection coin. But what determines which path the "boiling" atmosphere will take? Apparently the process is highly chaotic, and there appears to be no way to predict whether convection will result in open or closed cells. Indeed, the atmosphere may sometimes flip between one mode and another in no predictable pattern. Satellite: Aqua NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team To learn more about MODIS go to: rapidfire.sci.gsfc.nasa.gov/gallery/?latest NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe.

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.

Type-Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals

NASA Astrophysics Data System (ADS)

Zhao, Bin; Gu, Yu; Liou, Kuo-Nan; Wang, Yuan; Liu, Xiaohong; Huang, Lei; Jiang, Jonathan H.; Su, Hui

2018-04-01

Aerosol-cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9-year satellite retrievals, we find that, for convection-generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small-to-moderate aerosol loadings (<0.3 aerosol optical depth) and decrease with further aerosol increase. For in situ formed ice clouds, however, these cloud properties increase monotonically and more sharply with aerosol loadings. An increase in loading of smoke aerosols generally reduces cloud optical thickness of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution aerosols. These relationships between different cloud/aerosol types provide valuable constraints on the modeling assessment of aerosol-ice cloud radiative forcing.

Preparatory studies of zero-g cloud drop coalescence experiment

NASA Technical Reports Server (NTRS)

Telford, J. W.; Keck, T. S.

1979-01-01

Experiments to be performed in a weightless environment in order to study collision and coalescence processes of cloud droplets are described. Rain formation in warm clouds, formation of larger cloud drops, ice and water collision processes, and precipitation in supercooled clouds are among the topics covered.

A new subgrid-scale representation of hydrometeor fields using a multivariate PDF

DOE PAGES

Griffin, Brian M.; Larson, Vincent E.

2016-06-03

The subgrid-scale representation of hydrometeor fields is important for calculating microphysical process rates. In order to represent subgrid-scale variability, the Cloud Layers Unified By Binormals (CLUBB) parameterization uses a multivariate probability density function (PDF). In addition to vertical velocity, temperature, and moisture fields, the PDF includes hydrometeor fields. Previously, hydrometeor fields were assumed to follow a multivariate single lognormal distribution. Now, in order to better represent the distribution of hydrometeors, two new multivariate PDFs are formulated and introduced.The new PDFs represent hydrometeors using either a delta-lognormal or a delta-double-lognormal shape. The two new PDF distributions, plus the previous single lognormalmore » shape, are compared to histograms of data taken from large-eddy simulations (LESs) of a precipitating cumulus case, a drizzling stratocumulus case, and a deep convective case. In conclusion, the warm microphysical process rates produced by the different hydrometeor PDFs are compared to the same process rates produced by the LES.« less

A 15 year legacy of cloud and atmosphere observations in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Shupe, M.

2012-12-01

For the past 15 years, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program has operated the North Slope of Alaska (NSA) atmospheric observatory in Barrow, Alaska. Barrow offers many valuable perspectives on the Arctic environment that complement observations at lower latitudes. Unique features of the Arctic region include cold and dry atmospheric conditions, strong annual variability in sun light, a seasonally high-reflective surface, and persistent clouds that involve mixed-phase processes. ARM's ultimate objective with its flagship observatory at the northernmost point in U.S. territory is to provide measurements that can be used to improve the understanding of these atmospheric physical and radiative properties and processes such that they can be better represented in climate models. The NSA is the most detailed and long-lasting cloud-radiation-atmosphere observatory in the Arctic, providing continuous, sophisticated measurements of climate-relevant parameters. Instrument suites include active radars and lidars at various frequencies, passive radiometers monitoring radiation in microwave, infrared, visible and ultraviolet wavelengths, meteorological towers, and sounding systems. Together these measurements are used to characterize many of the important properties of clouds, aerosols, atmospheric radiation, dynamics, thermodynamics, and the surface. The coordinated nature of these measurements offers important multi-dimensional insight into many fundamental processes linking these different elements of the climate system. Moreover, the continuous operations of the facility support these observations over the full diurnal cycle and in all seasons of the year. This presentation will highlight a number of important studies and key findings that have been facilitated by the NSA observations during the first 15 years in operation. Some of these include: a thorough documentation of clouds, their occurrence frequency, phase, microphysical properties, and impacts on surface radiation; the indirect effect of aerosols on the surface longwave radiative effects of Arctic clouds; improved measurements of low amounts of atmospheric water vapor and their impacts on atmospheric radiation; dynamical and microphysical processes that are responsible for long-lived Arctic stratiform clouds; evaluation of satellite observations in extreme and observationally-difficult regimes; and assessment of model performance for models ranging from very high resolution to climate model simulations in the Arctic. The observational legacy at Barrow continues as ARM works to expand and enhance its impact. Plans are underway to install observational capabilities at a sister location in Oliktok Point to the east of Barrow, including enhanced capabilities of tethered balloon profiling and flying unmanned aerial vehicles over the adjacent Arctic Ocean. A new set of scanning cloud and precipitation radars have recently come online at Barrow that will allow for new insights on the spatial context of measurements at Barrow, including important information on the variability of atmospheric processes associated with the coastline. And lastly, there are many opportunities for the intensive observations at Barrow to inform important regional research on permafrost and sea-ice loss, while also serving as an unmatched, long-term record for evaluating atmospheric processes in regional and global climate models.

Microbiome of the upper troposphere: species composition and prevalence, effects of tropical storms, and atmospheric implications.

PubMed

DeLeon-Rodriguez, Natasha; Lathem, Terry L; Rodriguez-R, Luis M; Barazesh, James M; Anderson, Bruce E; Beyersdorf, Andreas J; Ziemba, Luke D; Bergin, Michael; Nenes, Athanasios; Konstantinidis, Konstantinos T

2013-02-12

The composition and prevalence of microorganisms in the middle-to-upper troposphere (8-15 km altitude) and their role in aerosol-cloud-precipitation interactions represent important, unresolved questions for biological and atmospheric science. In particular, airborne microorganisms above the oceans remain essentially uncharacterized, as most work to date is restricted to samples taken near the Earth's surface. Here we report on the microbiome of low- and high-altitude air masses sampled onboard the National Aeronautics and Space Administration DC-8 platform during the 2010 Genesis and Rapid Intensification Processes campaign in the Caribbean Sea. The samples were collected in cloudy and cloud-free air masses before, during, and after two major tropical hurricanes, Earl and Karl. Quantitative PCR and microscopy revealed that viable bacterial cells represented on average around 20% of the total particles in the 0.25- to 1-μm diameter range and were at least an order of magnitude more abundant than fungal cells, suggesting that bacteria represent an important and underestimated fraction of micrometer-sized atmospheric aerosols. The samples from the two hurricanes were characterized by significantly different bacterial communities, revealing that hurricanes aerosolize a large amount of new cells. Nonetheless, 17 bacterial taxa, including taxa that are known to use C1-C4 carbon compounds present in the atmosphere, were found in all samples, indicating that these organisms possess traits that allow survival in the troposphere. The findings presented here suggest that the microbiome is a dynamic and underappreciated aspect of the upper troposphere with potentially important impacts on the hydrological cycle, clouds, and climate.

The Vela Cloud: A Giant H I Anomaly in the NGC 3256 GROUP

NASA Astrophysics Data System (ADS)

English, Jayanne; Koribalski, B.; Bland-Hawthorn, J.; Freeman, K. C.; McCain, Claudia F.

2010-01-01

We present Australia Telescope Compact Array (ATCA) observations of a galaxy-sized intergalactic H I cloud ("the Vela Cloud") in the NGC 3256 galaxy group. The group contains the prominent merging galaxy NGC 3256, which is surrounded by a number of H I fragments, the tidally disturbed galaxy NGC 3263, and several other peculiar galaxies. The Vela Cloud, with an H I mass of 3-5 × 10^9 M_{⊙}, resides southeast of NGC 3256 and west of NGC 3263, within an area of 9' × 16' (100 kpc × 175 kpc for an adopted distance of 38 Mpc). In our ATCA data the Vela Cloud appears as three diffuse components and contains four density enhancements. The Vela Cloud's properties, together with its group environment, suggest that it has a tidal origin. Each density enhancement contains ˜ 10^{8} M_{⊙} of H I gas, which is sufficient material for the formation of globular cluster progenitors. However, if we represent the enhancements as Bonnor-Ebert spheres, then the pressure of the surrounding H I would need to increase by at least a factor of 9 in order to cause the collapse of an enhancement. Thus we do not expect them to form massive bound stellar systems like super star clusters or tidal dwarf galaxies. Since the H I density enhancements have some properties in common with high-velocity clouds, we explore whether they may evolve to be identified with these starless clouds instead. Original plate material is copyright © the Royal Observatory Edinburgh and the Anglo-Australian Observatory. The plates were processed into the present compressed digital form with their permission. The Digitized Sky Survey was produced at the Space Telescope Science Institute under US Government grant NAG W-2166.

Cloud Computing in Support of Applied Learning: A Baseline Study of Infrastructure Design at Southern Polytechnic State University

ERIC Educational Resources Information Center

Conn, Samuel S.; Reichgelt, Han

2013-01-01

Cloud computing represents an architecture and paradigm of computing designed to deliver infrastructure, platforms, and software as constructible computing resources on demand to networked users. As campuses are challenged to better accommodate academic needs for applications and computing environments, cloud computing can provide an accommodating…

A multi-sensor approach to the retrieval and model validation of global cloudiness

NASA Astrophysics Data System (ADS)

Miller, Steven D.

2000-11-01

The ephemeral clouds have represented a daunting challenge to the atmospheric modeling community from the very beginning. Our inability to resolve them by means of traditional passive sensors to the level of detail required for characterizing their complicated role in the climate feedback system has lead us to explore other resources at our disposal. This research seeks to illustrate and, where applicable, quantify the ways in which active (e.g., radar and lidar) remote sensing devices on existing and proposed platforms can serve to improve our current understanding of cloud and cloud processes in terms of (1)their role in the improvement of cloud property retrievals and (2)their application to the validation/development of clouds in numerical weather prediction models. A new retrieval technique which employs active sensors to constrain cloud boundaries in the vertical is shown to decrease the parameter uncertainties with respect to traditional passive methods in excess of 20% for effective particle radius, and 10-20% for optical depth when considering night-time retrievals of cirrus. These results are brought together with detailed cloud profile sampling from the Lidar In-space Technology Experiment (LITE) to conduct the first global-scale active sensor validation of ECMWF short-range forecasts. The comparisons display remarkable agreement in cloud spatial distribution. A weighted statistical analysis yields hit rates between 75-90%, threat scores 45-75%, probabilities of detection ~80%, and false alarm rates 10-45%. The results suggest that, given the level of realism displayed currently by the ECMWF prognostic cloud scheme forecasts, the reanalysis data may be considered as a new resource for global cloud information. A practical application of these findings has been outlined in the context of defining Cloud-Sat instrument requirements based on virtual orbital observations created from ECMWF global cloud distributions of liquid and ice water contents. This research gives cause for new hope in capturing the complex radiative, convective, and dynamical feedback mechanisms associated with clouds in the climate feedback system. Further, it appeals to the need for an improved collaborative rapport between the now largely disjoint modeling and measurement communities.

Aerosol, cloud, and precipitation interactions in Eastern North Atlantic

NASA Astrophysics Data System (ADS)

Wang, J.; Wood, R.; Dong, X.

2017-12-01

With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, ENA is periodically impacted by anthropogenic aerosol both from North American and from continental Europe, making it an excellent location to study the CCN budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA), funded by DOE Atmospheric Radiation Measurement (ARM) program, is designed to improve the understanding of marine boundary CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation in the ENA by combining airborne observations and long term surface based measurements. The study has two airborne deployments. The first deployment took place from June 15 to July 25, 2017, and the second one will take place from January 10 to February 20, 2018. Flights during the first deployment were carried out in the Azores, near the ARM ENA site on Graciosa Island. The long term measurements at the ENA site provide important Climatological context for the airborne observations during the two deployments, and the cloud structures provided by the scanning radars at the ENA site put the detailed in-situ measurements into mesoscale and cloud lifecycle contexts. Another important aspect of this study is to provide high quality in-situ measurements for validating and improving ground-based retrieval algorithms at the ENA site. This presentation will describe the setup and strategies of the study, early results from the first deployment on vertical structures and horizontal variabilities of aerosol properties, cloud and drizzle microphysics, and insights into the processes that drive the properties and interactions of aerosol and marine low clouds.

UV Raman lidar measurements of relative humidity for the characterization of cirrus cloud microphysical properties

NASA Astrophysics Data System (ADS)

di Girolamo, P.; Summa, D.; Lin, R.-F.; Maestri, T.; Rizzi, R.; Masiello, G.

2009-11-01

Raman lidar measurements performed in Potenza by the Raman lidar system BASIL in the presence of cirrus clouds are discussed. Measurements were performed on 6 September 2004 in the frame of the Italian phase of the EAQUATE Experiment. The major feature of BASIL is represented by its capability to perform high-resolution and accurate measurements of atmospheric temperature and water vapour, and consequently relative humidity, both in daytime and night-time, based on the application of the rotational and vibrational Raman lidar techniques in the UV. BASIL is also capable to provide measurements of the particle backscatter and extinction coefficient, and consequently lidar ratio (at the time of these measurements, only at one wavelength), which are fundamental to infer geometrical and microphysical properties of clouds. A case study is discussed in order to assess the capability of Raman lidars to measure humidity in presence of cirrus clouds, both below and inside the cloud. While air inside the cloud layers is observed to be always under-saturated with respect to water, both ice super-saturation and under-saturation conditions are found inside these clouds. Upper tropospheric moistening is observed below the lower cloud layer. The synergic use of the data derived from the ground based Raman Lidar and of spectral radiances measured by the NAST-I Airborne Spectrometer allows the determination of the temporal evolution of the atmospheric cooling/heating rates due to the presence of the cirrus cloud. Lidar measurements beneath the cirrus cloud layer have been interpreted using a 1-D cirrus cloud model with explicit microphysics. The 1-D simulations indicate that sedimentation-moistening has contributed significantly to the moist anomaly, but other mechanisms are also contributing. This result supports the hypothesis that the observed mid-tropospheric humidification is a real feature which is strongly influenced by the sublimation of precipitating ice crystals. Results illustrated in this study demonstrate that Raman lidars, like the one used in this study, can resolve the spatial and temporal scales required for the study of cirrus cloud microphysical processes and appear sensitive enough to reveal and quantify upper tropospheric humidification associated with cirrus cloud sublimation.

UV Raman lidar measurements of relative humidity for the characterization of cirrus cloud microphysical properties

NASA Astrophysics Data System (ADS)

di Girolamo, P.; Summa, D.; Lin, R.-F.; Maestri, T.; Rizzi, R.; Masiello, G.

2009-07-01

Raman lidar measurements performed in Potenza by the Raman lidar system BASIL in the presence of cirrus clouds are discussed. Measurements were performed on 6 September 2004 in the frame of Italian phase of the EAQUATE Experiment. The major feature of BASIL is represented by its capability to perform high-resolution and accurate measurements of atmospheric temperature and water vapour, and consequently relative humidity, both in daytime and night-time, based on the application of the rotational and vibrational Raman lidar techniques in the UV. BASIL is also capable to provide measurements of the particle backscatter and extinction coefficient, and consequently lidar ratio (at the time of these measurements only at one wavelength), which are fundamental to infer geometrical and microphysical properties of clouds. A case study is discussed in order to assess the capability of Raman lidars to measure humidity in presence of cirrus clouds, both below and inside the cloud. While air inside the cloud layers is observed to be always under-saturated with respect to water, both ice super-saturation and under-saturation conditions are found inside these clouds. Upper tropospheric moistening is observed below the lower cloud layer. The synergic use of the data derived from the ground based Raman Lidar and of spectral radiances measured by the NAST-I Airborne Spectrometer allows to determine the temporal evolution of the atmospheric cooling/heating rates due to the presence of the cirrus cloud anvil. Lidar measurements beneath the cirrus cloud layer have been interpreted using a 1-D cirrus cloud model with explicit microphysics. The 1-D simulations indicates that sedimentation-moistening has contributed significantly to the moist anomaly, but other mechanisms are also contributing. This result supports the hypothesis that the observed mid-tropospheric humidification is a real feature which is strongly influenced by the sublimation of precipitating ice crystals. Results illustrated in this study demonstrate that Raman lidars, like the one used in this study, can resolve the spatial and temporal scales required for the study of cirrus cloud microphysical processes and appears sensitive enough to reveal and quantify upper tropospheric humidification associated with cirrus cloud sublimation.

CLaMS-Ice: Large-scale cirrus cloud simulations in comparison with observations

NASA Astrophysics Data System (ADS)

Costa, Anja; Rolf, Christian; Grooß, Jens-Uwe; Spichtinger, Peter; Afchine, Armin; Spelten, Nicole; Dreiling, Volker; Zöger, Martin; Krämer, Martina

2016-04-01

Cirrus clouds are an element of uncertainty in the climate system and have received increasing attention since the last IPCC reports. The interactions of different freezing mechanisms, sedimentation rates, updraft velocity fluctuations and other factors that determine the formation and evolution of those clouds is still not fully understood. Thus, a reliable representation of cirrus clouds in models representing real atmospheric conditions is still a challenging task. At last year's EGU, Rolf et al. (2015) introduced the new large-scale microphysical cirrus cloud model CLaMS-Ice: based on trajectories calculated with CLaMS (McKenna et al., 2002 and Konopka et al. 2007), it simulates the development of cirrus clouds relying on the cirrus bulk model by Spichtinger and Gierens (2009). The qualitative agreement between CLaMS-Ice simulations and observations could be demonstrated at that time. Now we present a detailed quantitative comparison between standard ECMWF products, CLaMS-Ice simulations, and in-situ measurements obtained during the ML-Cirrus campaign 2014. We discuss the agreement of the parameters temperature (observational data: BAHAMAS), relative humidity (SHARC), cloud occurrence, cloud particle concentration, ice water content and cloud particle radii (all NIXE-CAPS). Due to the precise trajectories based on ECMWF wind and temperature fields, CLaMS-Ice represents the cirrus cloud vertical and horizontal coverage more accurately than the ECMWF ice water content (IWC) fields. We demonstrate how CLaMS-Ice can be used to evaluate different input settings (e.g. amount of ice nuclei, freezing thresholds, sedimentation settings) that lead to cirrus clouds with the microphysical properties observed during ML-Cirrus (2014).

Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, Thomas; Kalisch, John; Lorenz, Elke; Heinemann, Detlev

2016-03-01

Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Importance of aggregation and small ice crystals in cirrus clouds, based on observations and an ice particle growth model

NASA Technical Reports Server (NTRS)

Mitchell, David L.; Chai, Steven K.; Dong, Yayi; Arnott, W. Patrick; Hallett, John

1993-01-01

The 1 November 1986 FIRE I case study was used to test an ice particle growth model which predicts bimodal size spectra in cirrus clouds. The model was developed from an analytically based model which predicts the height evolution of monomodal ice particle size spectra from the measured ice water content (IWC). Size spectra from the monomodal model are represented by a gamma distribution, N(D) = N(sub o)D(exp nu)exp(-lambda D), where D = ice particle maximum dimension. The slope parameter, lambda, and the parameter N(sub o) are predicted from the IWC through the growth processes of vapor diffusion and aggregation. The model formulation is analytical, computationally efficient, and well suited for incorporation into larger models. The monomodal model has been validated against two other cirrus cloud case studies. From the monomodal size spectra, the size distributions which determine concentrations of ice particles less than about 150 mu m are predicted.

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.

Narrowing the Gap in Quantification of Aerosol-Cloud Radiative Effects

NASA Astrophysics Data System (ADS)

Feingold, G.; McComiskey, A. C.; Yamaguchi, T.; Kazil, J.; Johnson, J. S.; Carslaw, K. S.

2016-12-01

Despite large advances in our understanding of aerosol and cloud processes over the past years, uncertainty in the aerosol-cloud radiative effect/forcing is still of major concern. In this talk we will advocate a methodology for quantifying the aerosol-cloud radiative effect that considers the primacy of fundamental cloud properties such as cloud amount and albedo alongside the need for process level understanding of aerosol-cloud interactions. We will present a framework for quantifying the aerosol-cloud radiative effect, regime-by-regime, through process-based modelling and observations at the large eddy scale. We will argue that understanding the co-variability between meteorological and aerosol drivers of the radiative properties of the cloud system may be as important an endeavour as attempting to untangle these drivers.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Magic - Marine Arm Gpci Investigation of Clouds

NASA Astrophysics Data System (ADS)

Lewis, E. R.; Wiscombe, W. J.; Albrecht, B. A.; Bland, G.; Flagg, C. N.; Klein, S. A.; Kollias, P.; Mace, G. G.; Reynolds, M.; Schwartz, S. E.; Siebesma, P.; Teixeira, J.; Wood, R.; Zhang, M.

2012-12-01

MAGIC, the Marine ARM (Atmospheric Radiation Measurement program) GPCI Investigation of Clouds, will deploy the Second ARM Mobile Facility (AMF2) aboard the Horizon Lines cargo container ship M/V Spirit traversing the route between Los Angeles, CA and Honolulu, HI from October, 2012 through September, 2013 (except from a few months in the middle of this time period when the ship will be in dry dock). During this time AMF2 will observe and characterize the properties of clouds and precipitation, aerosols, and atmospheric radiation; standard meteorological and oceanographic variables; and atmospheric structure. There will also be Intensive Observational Periods (IOPs), one in January, 2013 and one in July, 2013 during which more detailed measurements of the atmospheric structure will be made. Clouds remain a major source of uncertainty in climate projections. In this context, subtropical marine boundary layer (MBL) clouds play a key role in cloud-climate feedbacks that are not well understood yet play a large role in biases both in seasonal coupled model forecasts and annual mean climate forecasts. In particular, current climate models do not accurately represent the transition from the stratocumulus (Sc) regime, with its high albedo and large impact on the global radiative balance of Earth, to shallow trade-wind cumulus (Cu), which play a fundamental role in global surface evaporation and also albedo. Climate models do not yet adequately parameterize the small-scale physical processes associated with turbulence, convection, and radiation in these clouds. Part of this inability results from lack of accurate data on these clouds and the conditions responsible for their properties, including aerosol properties, radiation, and atmospheric and oceanographic conditions. The primary objectives of MAGIC are to improve the representation of the Sc-to-Cu transition in climate models by characterizing the essential properties of this transition, and to produce the observed statistics of these Sc-to-Cu characteristics for the deployment period along the transect. This first marine deployment of AMF2 will yield an unparalleled and extremely rich data set that will greatly enhance the ability to understand and parameterize clouds and precipitation, aerosols, and radiation and the interactions among them; the processes that determine their properties; and factors that control these processes. Deployment of AMF2 on a ship that routinely traverses this route will provide a long-term data set over a vast cloud region which is of intense interest to climate modelers. Specifically, the proposed transect lies closely along the cross section used for the GPCI, and the data collected will provide constraint, validation, and support for this modeling effort, and for associated modeling efforts such as the CGILS and EUCLIPSE.

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

NASA Technical Reports Server (NTRS)

Page, William A.

1982-01-01

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

CloudSat Image of Tropical Thunderstorms Over Africa

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat image of a horizontal cross-section of tropical clouds and thunderstorms over east Africa. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, which the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudS at Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) visible image taken at nearly the same time.

Satellite Cloud and Radiative Property Processing and Distribution System on the NASA Langley ASDC OpenStack and OpenShift Cloud Platform

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Palikonda, R.; Smith, W. L., Jr.; Bedka, K. M.; Spangenberg, D.; Vakhnin, A.; Lutz, N. E.; Walter, J.; Kusterer, J.

2017-12-01

Cloud Computing offers new opportunities for large-scale scientific data producers to utilize Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) IT resources to process and deliver data products in an operational environment where timely delivery, reliability, and availability are critical. The NASA Langley Research Center Atmospheric Science Data Center (ASDC) is building and testing a private and public facing cloud for users in the Science Directorate to utilize as an everyday production environment. The NASA SatCORPS (Satellite ClOud and Radiation Property Retrieval System) team processes and derives near real-time (NRT) global cloud products from operational geostationary (GEO) satellite imager datasets. To deliver these products, we will utilize the public facing cloud and OpenShift to deploy a load-balanced webserver for data storage, access, and dissemination. The OpenStack private cloud will host data ingest and computational capabilities for SatCORPS processing. This paper will discuss the SatCORPS migration towards, and usage of, the ASDC Cloud Services in an operational environment. Detailed lessons learned from use of prior cloud providers, specifically the Amazon Web Services (AWS) GovCloud and the Government Cloud administered by the Langley Managed Cloud Environment (LMCE) will also be discussed.

A Novel College Network Resource Management Method using Cloud Computing

NASA Astrophysics Data System (ADS)

Lin, Chen

At present information construction of college mainly has construction of college networks and management information system; there are many problems during the process of information. Cloud computing is development of distributed processing, parallel processing and grid computing, which make data stored on the cloud, make software and services placed in the cloud and build on top of various standards and protocols, you can get it through all kinds of equipments. This article introduces cloud computing and function of cloud computing, then analyzes the exiting problems of college network resource management, the cloud computing technology and methods are applied in the construction of college information sharing platform.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

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

Evans, Stuart; Marchand, Roger; Ackerman, Thomas

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

NASA Astrophysics Data System (ADS)

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; Donner, Leo; Golaz, Jean-Christophe; Seman, Charles

2017-12-01

We define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. We find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

DOE PAGES

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; ...

2017-11-16

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

ARM Climate Research Facility Annual Report 2004

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

Voyles, J.

2004-12-31

Like a rock that slowly wears away beneath the pressure of a waterfall, planet earth?s climate is almost imperceptibly changing. Glaciers are getting smaller, droughts are lasting longer, and extreme weather events like fires, floods, and tornadoes are occurring with greater frequency. Why? Part of the answer is clouds and the amount of solar radiation they reflect or absorb. These two factors clouds and radiative transfer represent the greatest source of error and uncertainty in the current generation of general circulation models used for climate research and simulation. The U.S. Global Change Research Act of 1990 established an interagency programmore » within the Executive Office of the President to coordinate U.S. agency-sponsored scientific research designed to monitor, understand, and predict changes in the global environment. To address the need for new research on clouds and radiation, the U.S. Department of Energy (DOE) established the Atmospheric Radiation Measurement (ARM) Program. As part of the DOE?s overall Climate Change Science Program, a primary objective of the ARM Program is improved scientific understanding of the fundamental physics related to interactions between clouds and radiative feedback processes in the atmosphere.« less

A scalable approach for tree segmentation within small-footprint airborne LiDAR data

NASA Astrophysics Data System (ADS)

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

2017-05-01

This paper presents a distributed approach that scales up to segment tree crowns within a LiDAR point cloud representing an arbitrarily large forested area. The approach uses a single-processor tree segmentation algorithm as a building block in order to process the data delivered in the shape of tiles in parallel. The distributed processing is performed in a master-slave manner, in which the master maintains the global map of the tiles and coordinates the slaves that segment tree crowns within and across the boundaries of the tiles. A minimal bias was introduced to the number of detected trees because of trees lying across the tile boundaries, which was quantified and adjusted for. Theoretical and experimental analyses of the runtime of the approach revealed a near linear speedup. The estimated number of trees categorized by crown class and the associated error margins as well as the height distribution of the detected trees aligned well with field estimations, verifying that the distributed approach works correctly. The approach enables providing information of individual tree locations and point cloud segments for a forest-level area in a timely manner, which can be used to create detailed remotely sensed forest inventories. Although the approach was presented for tree segmentation within LiDAR point clouds, the idea can also be generalized to scale up processing other big spatial datasets.

MODIS Direct Broadcast and Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2004-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

Observations and Model Simulations of Orographic Mixed-Phase Clouds at Mountain Range Site

NASA Astrophysics Data System (ADS)

Lohmann, U.; Henneberg, O. C.; Henneberger, J.

2014-12-01

Aerosol-cloud interactions constitute the highest uncertainties in forcing estimation. Especially uncertainties due to mixed clouds (MPCs) have a large impact on the radiative balance and precipitation prediction. Due to Wegener-Bergeron-Findeisen-process (WBF) which describes glaciation of MPCs due to the lower saturation over ice than over water, MPCs are mostly expected as short lived clouds. In contrast to the theory of the WBF, in-situ measurements have shown that MPCs can persist over longer time. But only a small number of measurements of MPCs is available. In addition modeling studies about MPCs are difficult as their processes of the three-phase-system are on the micro scale and therefore not resolved in models. We present measurements obtained at the high-altitude research station Jungfraujoch (JFJ, 3580 m asl) in the Swiss Alps partly taken during the CLoud-Aerosol Interaction Experiments (CLACE). During the winter season, the JFJ has a high frequency of super-cooled clouds and is considered representative for being in the free troposphere. In-situ measurements of the microstructure of MPCs have been obtained with the digital imager HOLIMO, that delivers phase-resolved size distributions, concentrations, and water contents. The data set of MPCs at JFJ shows that for northerly wind cases partially-glaciated MPCs are more frequently observed than for southerly wind cases. The higher frequency of these intermediate states of MPCs suggests either higher updraft velocities, and therefore higher water-vapor supersaturations, or the absence of sufficiently high IN concentrations to quickly glaciate the MPC. Because of the limitation of in-situ information, i.e. point measurements and missing measurements of vertical velocities at JFJ, the mechanism of the long persistence of MPCs cannot be fully understood. Therefore, in addition to measurements we will investigate the JFJ region with a model study with the non-hydrostatic model COSMO-ART-M7. Combination of km-scale simulation with measurements allows to systematically study the effect of vertical velocity and temperatures on MPCs at JFJ, the synoptic conditions, origins of air masses, aerosol and IN concentrations. Comparison between in-situ measurements will also help to improve parametrization of microphysical processes in the model.

Petri net modeling of encrypted information flow in federated cloud

NASA Astrophysics Data System (ADS)

Khushk, Abdul Rauf; Li, Xiaozhong

2017-08-01

Solutions proposed and developed for the cost-effective cloud systems suffer from a combination of secure private clouds and less secure public clouds. Need to locate applications within different clouds poses a security risk to the information flow of the entire system. This study addresses this by assigning security levels of a given lattice to the entities of a federated cloud system. A dynamic flow sensitive security model featuring Bell-LaPadula procedures is explored that tracks and authenticates the secure information flow in federated clouds. Additionally, a Petri net model is considered as a case study to represent the proposed system and further validate the performance of the said system.

ARC-1989-AC89-0114-324

NASA Image and Video Library

1989-02-28

Arctic Ozone Expedition Stavanger Norway These clouds in the polar regions north of Stravanger, Norway are representative of what are called 'Type 1' and Type 2' polar stratospheric clouds. Type 1 are seen in the lower portion and consist of cloud particles comprised of nitrogen trihydrates. Seen edge-on as in this view, they appear as a thin dark orange or brown layer. Multiple layering can be seen. The Type 2 clouds are above and consist mostly of water molecules frozen as ice. The size of the particles in Type 2 clouds, the water-ice clouds, are much larger than the particle size of the Type 1 clouds - which are on the order of the wavelength of light.

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

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

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 developmore » 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.« less

Extraction of Profile Information from Cloud Contaminated Radiances. Appendixes 2

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Huang, H.-L.; Li, Jun; Liu, X.; Larar, A. M.

2003-01-01

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

A Comparison of Parameterizations of Secondary Organic Aerosol Production: Global Budget and Spatiotemporal Variability

NASA Astrophysics Data System (ADS)

Liu, J.; Chen, Z.; Horowitz, L. W.; Carlton, A. M. G.; Fan, S.; Cheng, Y.; Ervens, B.; Fu, T. M.; He, C.; Tao, S.

2014-12-01

Secondary organic aerosols (SOA) have a profound influence on air quality and climate, but large uncertainties exist in modeling SOA on the global scale. In this study, five SOA parameterization schemes, including a two-product model (TPM), volatility basis-set (VBS) and three cloud SOA schemes (Ervens et al. (2008, 2014), Fu et al. (2008) , and He et al. (2013)), are implemented into the global chemical transport model (MOZART-4). For each scheme, model simulations are conducted with identical boundary and initial conditions. The VBS scheme produces the highest global annual SOA production (close to 35 Tg·y-1), followed by three cloud schemes (26-30 Tg·y-1) and TPM (23 Tg·y-1). Though sharing a similar partitioning theory to the TPM scheme, the VBS approach simulates the chemical aging of multiple generations of VOCs oxidation products, resulting in a much larger SOA source, particularly from aromatic species, over Europe, the Middle East and Eastern America. The formation of SOA in VBS, which represents the net partitioning of semi-volatile organic compounds from vapor to condensed phase, is highly sensitivity to the aging and wet removal processes of vapor-phase organic compounds. The production of SOA from cloud processes (SOAcld) is constrained by the coincidence of liquid cloud water and water-soluble organic compounds. Therefore, all cloud schemes resolve a fairly similar spatial pattern over the tropical and the mid-latitude continents. The spatiotemporal diversity among SOA parameterizations is largely driven by differences in precursor inputs. Therefore, a deeper understanding of the evolution, wet removal, and phase partitioning of semi-volatile organic compounds, particularly above remote land and oceanic areas, is critical to better constrain the global-scale distribution and related climate forcing of secondary organic aerosols.

Comparison of the different approaches to generate holograms from data acquired with a Kinect sensor

NASA Astrophysics Data System (ADS)

Kang, Ji-Hoon; Leportier, Thibault; Ju, Byeong-Kwon; Song, Jin Dong; Lee, Kwang-Hoon; Park, Min-Chul

2017-05-01

Data of real scenes acquired in real-time with a Kinect sensor can be processed with different approaches to generate a hologram. 3D models can be generated from a point cloud or a mesh representation. The advantage of the point cloud approach is that computation process is well established since it involves only diffraction and propagation of point sources between parallel planes. On the other hand, the mesh representation enables to reduce the number of elements necessary to represent the object. Then, even though the computation time for the contribution of a single element increases compared to a simple point, the total computation time can be reduced significantly. However, the algorithm is more complex since propagation of elemental polygons between non-parallel planes should be implemented. Finally, since a depth map of the scene is acquired at the same time than the intensity image, a depth layer approach can also be adopted. This technique is appropriate for a fast computation since propagation of an optical wavefront from one plane to another can be handled efficiently with the fast Fourier transform. Fast computation with depth layer approach is convenient for real time applications, but point cloud method is more appropriate when high resolution is needed. In this study, since Kinect can be used to obtain both point cloud and depth map, we examine the different approaches that can be adopted for hologram computation and compare their performance.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Examining Effects of Virtual Machine Settings on Voice over Internet Protocol in a Private Cloud Environment

ERIC Educational Resources Information Center

Liao, Yuan

2011-01-01

The virtualization of computing resources, as represented by the sustained growth of cloud computing, continues to thrive. Information Technology departments are building their private clouds due to the perception of significant cost savings by managing all physical computing resources from a single point and assigning them to applications or…

The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study

NASA Astrophysics Data System (ADS)

Grosvenor, Daniel P.; Field, Paul R.; Hill, Adrian A.; Shipway, Benjamin J.

2017-04-01

Aerosol-cloud interactions are explored using 1 km simulations of a case study of predominantly closed-cell SE Pacific stratocumulus clouds. The simulations include realistic meteorology along with newly implemented cloud microphysics and sub-grid cloud schemes. The model was critically assessed against observations of liquid water path (LWP), broadband fluxes, cloud fraction (fc), droplet number concentrations (Nd), thermodynamic profiles, and radar reflectivities.Aerosol loading sensitivity tests showed that at low aerosol loadings, changes to aerosol affected shortwave fluxes equally through changes to cloud macrophysical characteristics (LWP, fc) and cloud albedo changes due solely to Nd changes. However, at high aerosol loadings, only the Nd albedo change was important. Evidence was also provided to show that a treatment of sub-grid clouds is as important as order of magnitude changes in aerosol loading for the accurate simulation of stratocumulus at this grid resolution.Overall, the control model demonstrated a credible ability to reproduce observations, suggesting that many of the important physical processes for accurately simulating these clouds are represented within the model and giving some confidence in the predictions of the model concerning stratocumulus and the impact of aerosol. For example, the control run was able to reproduce the shape and magnitude of the observed diurnal cycle of domain mean LWP to within ˜ 10 g m-2 for the nighttime, but with an overestimate for the daytime of up to 30 g m-2. The latter was attributed to the uniform aerosol fields imposed on the model, which meant that the model failed to include the low-Nd mode that was observed further offshore, preventing the LWP removal through precipitation that likely occurred in reality. The boundary layer was too low by around 260 m, which was attributed to the driving global model analysis. The shapes and sizes of the observed bands of clouds and open-cell-like regions of low areal cloud cover were qualitatively captured. The daytime fc frequency distribution was reproduced to within Δfc = 0.04 for fc > ˜ 0.7 as was the domain mean nighttime fc (at a single time) to within Δfc = 0.02. Frequency distributions of shortwave top-of-the-atmosphere (TOA) fluxes from the satellite were well represented by the model, with only a slight underestimate of the mean by 15 %; this was attributed to near-shore aerosol concentrations that were too low for the particular times of the satellite overpasses. TOA long-wave flux distributions were close to those from the satellite with agreement of the mean value to within 0.4 %. From comparisons of Nd distributions to those from the satellite, it was found that the Nd mode from the model agreed with the higher of the two observed modes to within ˜ 15 %.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Study on wet scavenging of atmospheric pollutants in south Brazil

NASA Astrophysics Data System (ADS)

Wiegand, Flavio; Pereira, Felipe Norte; Teixeira, Elba Calesso

2011-09-01

The present paper presents the study of in-cloud and below-cloud SO 2 and SO 42-scavenging processes by applying numerical models in the Candiota region, located in the state of Rio Grande do Sul, South Brazil. The BRAMS (Brazilian Regional Atmospheric Modeling System) model was applied to simulate the vertical structure of the clouds, and the B.V.2 (Below-Cloud Beheng Version 2) scavenging model was applied to simulate in-cloud and below-cloud scavenging processes of the pollutants SO 2 and SO 42-. Five events in 2004 were selected for this study and were sampled at the Candiota Airport station. The concentrations of SO 2 and SO 42- sampled in the air and the simulated meteorological parameters of rainfall episodes were used as input data in the B.V.2, which simulates raindrop interactions associated with the scavenging process. Results for the Candiota region showed that in-cloud scavenging processes were more significant than below-cloud scavenging processes for two of the five events studied, with a contribution of approximately 90-100% of SO 2 and SO 42- concentrations in rainwater. A few adjustments to the original version of B.V.2 were made to allow simulation of scavenging processes in several types of clouds, not only cumulus humilis and cumulus congestus.

Stable isotope composition of waters in the Great Basin, United States 1. Air-mass trajectories

USGS Publications Warehouse

Friedman, I.; Harris, J.M.; Smith, G.I.; Johnson, C.A.

2002-01-01

Isentropic trajectories, calculated using the NOAA/Climate Monitoring and Diagnostics Laboratory's isentropic transport model, were used to determine air-parcel origins and the influence of air mass trajectories on the isotopic composition of precipitation events that occurred between October 1991 and September 1993 at Cedar City, Utah, and Winnemucca, Nevada. Examination of trajectories that trace the position of air parcels backward in time for 10 days indicated five distinct regions of water vapor origin: (1) Gulf of Alaska and North Pacific, (2) central Pacific, (3) tropical Pacific, (4) Gulf of Mexico, and (5) continental land mass. Deuterium (??D) and oxygen-18 (??18O) analyses were made of precipitation representing 99% of all Cedar City events. Similar analyses were made on precipitation representing 66% of the precipitation falling at Winnemucca during the same period. The average isotopic composition of precipitation derived from each water vapor source was determined. More than half of the precipitation that fell at both sites during the study period originated in the tropical Pacific and traveled northeast to the Great Basin; only a small proportion traversed the Sierra Nevada. The isotopic composition of precipitation is determined by air-mass origin and its track to the collection station, mechanism of droplet formation, reequilibration within clouds, and evaporation during its passage from cloud to ground. The Rayleigh distillation model can explain the changes in isotopic composition of precipitation as an air mass is cooled pseudo-adiabatically during uplift. However, the complicated processes that take place in the rapidly convecting environment of cumulonimbus and other clouds that are common in the Great Basin, especially in summer, require modification of this model because raindrops that form in the lower portion of those clouds undergo isotopic change as they are elevated to upper levels of the clouds from where they eventually drop to the ground.

An efficient framework for modeling clouds from Landsat8 images

NASA Astrophysics Data System (ADS)

Yuan, Chunqiang; Guo, Jing

2015-03-01

Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.

Tropical Diabatic Heating and the Role of Convective Processes as Represented in Several Contemporary Climate Models

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Roads, John; Oglesby, Robert; Marshall, Susan

2004-01-01

One of the most fundamental properties of the global heat balance is the net heat input into the tropical atmosphere that helps drive the planetary atmospheric circulation. Although broadly understood in terms of its gross structure and balance of source / sink terms, incorporation of the relevant processes in predictive models is still rather poor. The work reported here examines the tropical radiative and water cycle behavior as produced by four contemporary climate models. Among these are the NSIPP-2 (NASA Seasonal to Interannual Prediction Project) which uses the RAS convective parameterization; the FVCCM, a code using finite volume numerics and the CCM3.6 physics; FVCCM-MCRAS again having the finite volume numerics, but MCRAS convective parameterization and a different radiation treatment; and, finally, the NCEP GSM which uses the RAS. Using multi-decadal integrations with specified SSTs we examine the statistics of radiative / convective processes and associated energy transports, and then estimate model energy flux sensitivities to SST changes. In particular the behavior of the convective parameterizations is investigated. Additional model integrations are performed specifically to assess the importance representing convective inhibition in regulating convective cloud-top structure and moisture detrainment as well as controlling surface energy fluxes. To evaluate the results of these experiments, a number of satellite retrievals are used: TRMM retrievals of vertical reflectivity structure, rainfall rate, and inferred diabatic heating are analyzed to show both seasonal and interannual variations in vertical structure of latent heat release. Top-of-atmosphere radiative fluxes from ERBS and CERES are used to examine shortwave and longwave cloud forcing and to deduce required seasonal energy transports. Retrievals of cloud properties from ISCCP and water vapor variations from SSM/T-2 are also used to understand behavior of the humidity fields. These observations are supplemented with output form the DOE Reanalysis-2.

Enabling Earth Science Through Cloud Computing

NASA Technical Reports Server (NTRS)

Hardman, Sean; Riofrio, Andres; Shams, Khawaja; Freeborn, Dana; Springer, Paul; Chafin, Brian

2012-01-01

Cloud Computing holds tremendous potential for missions across the National Aeronautics and Space Administration. Several flight missions are already benefiting from an investment in cloud computing for mission critical pipelines and services through faster processing time, higher availability, and drastically lower costs available on cloud systems. However, these processes do not currently extend to general scientific algorithms relevant to earth science missions. The members of the Airborne Cloud Computing Environment task at the Jet Propulsion Laboratory have worked closely with the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to integrate cloud computing into their science data processing pipeline. This paper details the efforts involved in deploying a science data system for the CARVE mission, evaluating and integrating cloud computing solutions with the system and porting their science algorithms for execution in a cloud environment.

Individual aerosol particles in and below clouds along a Mt. Fuji slope: Modification of sea-salt-containing particles by in-cloud processing

NASA Astrophysics Data System (ADS)

Ueda, S.; Hirose, Y.; Miura, K.; Okochi, H.

2014-02-01

Sizes and compositions of atmospheric aerosol particles can be altered by in-cloud processing by absorption/adsorption of gaseous and particulate materials and drying of aerosol particles that were formerly activated as cloud condensation nuclei. To elucidate differences of aerosol particles before and after in-cloud processing, aerosols were observed along a slope of Mt. Fuji, Japan (3776 m a.s.l.) during the summer in 2011 and 2012 using a portable laser particle counter (LPC) and an aerosol sampler. Aerosol samples for analyses of elemental compositions were obtained using a cascade impactor at top-of-cloud, in-cloud, and below-cloud altitudes. To investigate composition changes via in-cloud processing, individual particles (0.5-2 μm diameter) of samples from five cases (days) collected at different altitudes under similar backward air mass trajectory conditions were analyzed using a transmission electron microscope (TEM) equipped with an energy dispersive X-ray analyzer. For most cases (four cases), most particles at all altitudes mainly comprised sea salts: mainly Na with some S and/or Cl. Of those, in two cases, sea-salt-containing particles with Cl were found in below-cloud samples, although sea-salt-containing particles in top-of-cloud samples did not contain Cl. This result suggests that Cl in the sea salt was displaced by other cloud components. In the other two cases, sea-salt-containing particles on samples at all altitudes were without Cl. However, molar ratios of S to Na (S/Na) of the sea-salt-containing particles of top-of-cloud samples were higher than those of below-cloud samples, suggesting that sulfuric acid or sulfate was added to sea-salt-containing particles after complete displacement of Cl by absorption of SO2 or coagulation with sulfate. The additional volume of sulfuric acid in clouds for the two cases was estimated using the observed S/Na values of sea-salt-containing particles. The estimation revealed that size changes by in-cloud processing from below-cloud to top-of-cloud altitudes were less than 6% for sizes of 0.5-2 μm diameter. The obtained results will be useful to evaluate the aging effect and transition of aerosol particles through in-cloud processing.

Vertical distribution of microphysical properties of Arctic springtime low-level mixed-phase clouds over the Greenland and Norwegian seas

NASA Astrophysics Data System (ADS)

Mioche, Guillaume; Jourdan, Olivier; Delanoë, Julien; Gourbeyre, Christophe; Febvre, Guy; Dupuy, Régis; Monier, Marie; Szczap, Frédéric; Schwarzenboeck, Alfons; Gayet, Jean-François

2017-10-01

This study aims to characterize the microphysical and optical properties of ice crystals and supercooled liquid droplets within low-level Arctic mixed-phase clouds (MPCs). We compiled and analyzed cloud in situ measurements from four airborne spring campaigns (representing 18 flights and 71 vertical profiles in MPCs) over the Greenland and Norwegian seas mainly in the vicinity of the Svalbard archipelago. Cloud phase discrimination and representative vertical profiles of the number, size, mass and shape of ice crystals and liquid droplets are established. The results show that the liquid phase dominates the upper part of the MPCs. High concentrations (120 cm-3 on average) of small droplets (mean values of 15 µm), with an averaged liquid water content (LWC) of 0.2 g m-3 are measured at cloud top. The ice phase dominates the microphysical properties in the lower part of the cloud and beneath it in the precipitation region (mean values of 100 µm, 3 L-1 and 0.025 g m-3 for diameter, particle concentration and ice water content (IWC), respectively). The analysis of the ice crystal morphology shows that the majority of ice particles are irregularly shaped or rimed particles; the prevailing regular habits found are stellars and plates. We hypothesize that riming and diffusional growth processes, including the Wegener-Bergeron-Findeisen (WBF) mechanism, are the main growth mechanisms involved in the observed MPCs. The impact of larger-scale meteorological conditions on the vertical profiles of MPC properties was also investigated. Large values of LWC and high concentration of smaller droplets are possibly linked to polluted situations and air mass origins from the south, which can lead to very low values of ice crystal size and IWC. On the contrary, clean situations with low temperatures exhibit larger values of ice crystal size and IWC. Several parameterizations relevant for remote sensing or modeling studies are also determined, such as IWC (and LWC) - extinction relationship, ice and liquid integrated water paths, ice concentration and liquid water fraction according to temperature.

Segmentation of Large Unstructured Point Clouds Using Octree-Based Region Growing and Conditional Random Fields

NASA Astrophysics Data System (ADS)

Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.

2017-11-01

Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.

Small-Scale Spatial Variability of Ice Supersaturation and Cirrus in the TTL

NASA Astrophysics Data System (ADS)

DiGangi, J. P.; Podolske, J. R.; Rana, M.; Slate, T. A.; Diskin, G. S.

2014-12-01

The processes controlling cloud formation and evolution represent a significant uncertainty in models of global climate change. High altitude cirrus clouds contribute a large portion of this uncertainty due to their altitude and abundance. The mechanism behind the formation of cirrus clouds depends on the characteristics and composition of ice supersaturation (ISS) regions, regions where the relative humidity with respect to ice (RHi) is greater than 100%. Small-scale dynamics have recently been shown to have a strong effect on the RHi of the UT/LS, and therefore on cirrus cloud formation. Until now, there has been insufficient data in the Tropical Tropopause Layer (TTL) to investigate these effects. The Airborne Tropical TRopopause EXperiment (ATTREX) was a series of campaigns focused on improving our understanding of humidity in the TTL. During this campaign, the NASA Langley/Ames Diode Laser Hygrometer was part of the payload on the NASA Global Hawk, resulting in measurements of humidity with as low as 1-2 m vertical resolution at altitudes up to 19 km. We will present observations from ATTREX describing the small scale spatial variability of water vapor along transects of ISSRs and cirrus clouds, as well as the dynamics driving the formation of ISS regions. These results will be discussed in context with results from prior UT/LS campaigns, such as DC3 and HIPPO.

The Relationships Between Insoluble Precipitation Residues, Clouds, and Precipitation Over California's Southern Sierra Nevada During Winter Storms

NASA Technical Reports Server (NTRS)

Creamean, Jessie M.; White, Allen B.; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Douglas A.; Prather, Kimberly A.

2016-01-01

Ice formation in orographic mixed-phase clouds can enhance precipitation and depends on the type of aerosols that serve as ice nucleating particles (INP). The resulting precipitation from these clouds is a viable source of water, especially for regions such as the California Sierra Nevada. Thus, a better understanding of the sources of INP that impact orographic clouds is important for assessing water availability in California. This study presents a multi-site, multi-year analysis of single particle insoluble residues in precipitation samples that likely influenced cloud ice and precipitation formation above Yosemite National Park. Dust and biological particles represented the dominant fraction of the residues (64% on average). Cloud glaciation, determined using GOES satellite observations, not only depended on high cloud tops (greater than 6.2 km) and low temperatures (less than -26 C), but also on the composition of the dust and biological residues. The greatest prevalence of ice-phase clouds occurred in conjunction with biologically-rich residues and mineral dust rich in calcium, followed by iron and aluminosilicates. Dust and biological particles are known to be efficient INP, thus these residues are what likely influenced ice formation in clouds above the sites and subsequent precipitation quantities reaching the surface during events with similar meteorology. The goal of this study is to use precipitation chemistry information to gain a better understanding of the potential sources of INP in the south-central Sierra Nevada, where cloud-aerosol-precipitation interactions are under-studied and where mixed-phase orographic clouds represent a key element in the generation of precipitation and thus the water supply in California.

Cloud Microphysics Budget in the Tropical Deep Convective Regime

NASA Technical Reports Server (NTRS)

Li, Xiao-Fan; Sui, C.-H.; Lau, K.-M.; Einaudi, Franco (Technical Monitor)

2001-01-01

Cloud microphysics budgets in the tropical deep convective regime are analyzed based on a 2-D cloud resolving simulation. The model is forced by the large-scale vertical velocity and zonal wind and large-scale horizontal advections derived from TOGA COARE for a 20-day period. The role of cloud microphysics is first examined by analyzing mass-weighted mean heat budget and column-integrated moisture budget. Hourly budgets show that local changes of mass-weighted mean temperature and column-integrated moisture are mainly determined by the residuals between vertical thermal advection and latent heat of condensation and between vertical moisture advection and condensation respectively. Thus, atmospheric thermodynamics depends on how cloud microphysical processes are parameterized. Cloud microphysics budgets are then analyzed for raining conditions. For cloud-vapor exchange between cloud system and its embedded environment, rainfall and evaporation of raindrop are compensated by the condensation and deposition of supersaturated vapor. Inside the cloud system, the condensation of supersaturated vapor balances conversion from cloud water to raindrop, snow, and graupel through collection and accretion processes. The deposition of supersaturated vapor balances conversion from cloud ice to snow through conversion and riming processes. The conversion and riming of cloud ice and the accretion of cloud water balance conversion from snow to graupel through accretion process. Finally, the collection of cloud water and the melting of graupel increase raindrop to compensate the loss of raindrop due to rainfall and the evaporation of raindrop.

The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM

NASA Astrophysics Data System (ADS)

Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.

2017-12-01

Mixed phase clouds remain a leading source of uncertainty in our attempt to quantify cloud-climate and aerosol-cloud climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution cloud modelling, and retrievals of cloud phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the cloud phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the cloud provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in cloud and cloud top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective cloud simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of cloud phase to primary ice formation, cloud ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in cloud and cloud top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase clouds.

Mapping the Impact of Aerosol-Cloud Interactions on Cloud Formation and Warm-season Rainfall in Mountainous Regions Using Observations and Models

NASA Astrophysics Data System (ADS)

Duan, Yajuan

Light rainfall (< 3 mm/hr) amounts to 30-70% of the annual water budget in the Southern Appalachian Mountains (SAM), a mid-latitude mid-mountain system in the SE CONUS. Topographic complexity favors the diurnal development of regional-scale convergence patterns that provide the moisture source for low-level clouds and fog (LLCF). Low-level moisture and cloud condensation nuclei (CCN) are distributed by ridge-valley circulations favoring LLCF formation that modulate the diurnal cycle of rainfall especially the mid-day peak. The overarching objective of this dissertation is to advance the quantitative understanding of the indirect effect of aerosols on the diurnal cycle of LLCF and warm-season precipitation in mountainous regions generally, and in the SAM in particular, for the purpose of improving the representation of orographic precipitation processes in remote sensing retrievals and physically-based models. The research approach consists of integrating analysis of in situ observations from long-term observation networks and an intensive field campaign, multi-sensor satellite data, and modeling studies. In the first part of this dissertation, long-term satellite observations are analyzed to characterize the spatial and temporal variability of LLCF and to elucidate the physical basis of the space-time error structure in precipitation retrievals. Significantly underestimated precipitation errors are attributed to variations in low-level rainfall microstructure undetected by satellites. Column model simulations including observed LLCF microphysics demonstrate that seeder-feeder interactions (SFI) among upper-level precipitation and LLCF contribute to an three-fold increase in observed rainfall accumulation and can enhance surface rainfall by up to ten-fold. The second part of this dissertation examines the indirect effect of aerosols on cloud formation and warm-season daytime precipitation in the SAM. A new entraining spectral cloud parcel model was developed and applied to provide the first assessment of aerosol-cloud interactions in the early development of mid-day cumulus congestus over the inner SAM. Leveraging comprehensive measurements from the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014, model results indicate that simulated spectra with a low value of condensation coefficient (0.01) are in good agreement with IPHEx aircraft observations. Further, to explore sensitivity of warm-season precipitation processes to CCN characteristics, detailed intercomparisons of Weather Research and Forecasting (WRF) model simulations using IPHEx and standard continental CCN spectra were conducted. The simulated CDNC using the local spectrum show better agreement with IPHEx airborne observations and better replicate the widespread low-level cloudiness around mid-day over the inner region. The local spectrum simulation also indicate suppressed early precipitation, enhanced ice processes tied to more vigorous vertical development of individual storm cells. The studied processes here are representative of dominant moist atmospheric processes in complex terrain and cloud forests in the humid tropics and extra-tropics, thus findings from this research in the SAM are transferable to mountainous areas elsewhere.

Simulating the Effects of Semivolatile Compounds on Cloud Processing of Aerosol

NASA Astrophysics Data System (ADS)

Kokkola, H.; Kudzotsa, I.; Tonttila, J.; Raatikainen, T.; Romakkaniemi, S.

2017-12-01

Aerosol removal processes largely dictate how well aerosol is transported in the atmosphere and thus the aerosol load over remote regions depends on how effectively aerosol is removed during its transport from the source regions. This means that in order to model the global distribution aerosol, both in vertical and horizontal, wet deposition processes have to be properly modelled. However, in large scale models, the description of wet removal and the vertical redistribution of aerosol by cloud processes is often extremely simplified.Here we present a novel aerosol-cloud model SALSA, where the aerosol properties are tracked through different cloud processes. These processes include: cloud droplet activation, precipitation formation, ice nucleation, melting, and evaporation. It is a sectional model that includes separate size sections for non-activated aerosol, cloud droplets, precipitation droplets, and ice crystals. The aerosol-cloud model was coupled to a large eddy model UCLALES which simulates the boundary-layer dynamics. In this study, the model has been applied in studying the wet removal as well as interactions between aerosol, clouds, and semi-volatile compounds, ammonia and nitric acid. These semi-volative compounds are special in the sense that they co-condense together with water during cloud activation and have been suggested to form droplets that can be considered cloud-droplet-like already in subsaturated conditions. In our model, we calculate the kinetic partitioning of ammonia and sulfate thus explicitly taking into account the effect of ammonia and nitric acid in the cloud formation. Our simulations indicate that especially in polluted conditions, these compounds significantly affect the properties of cloud droplets thus significantly affecting the lifecycle of different aerosol compounds.

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

NASA Technical Reports Server (NTRS)

Brown, Richard B.; Smoot, James C.; Underwood, Lauren; Armstrong, C. Duane

2012-01-01

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Developing cloud-based Business Process Management (BPM): a survey

NASA Astrophysics Data System (ADS)

Mercia; Gunawan, W.; Fajar, A. N.; Alianto, H.; Inayatulloh

2018-03-01

In today’s highly competitive business environment, modern enterprises are dealing difficulties to cut unnecessary costs, eliminate wastes and delivery huge benefits for the organization. Companies are increasingly turning to a more flexible IT environment to help them realize this goal. For this reason, the article applies cloud based Business Process Management (BPM) that enables to focus on modeling, monitoring and process management. Cloud based BPM consists of business processes, business information and IT resources, which help build real-time intelligence systems, based on business management and cloud technology. Cloud computing is a paradigm that involves procuring dynamically measurable resources over the internet as an IT resource service. Cloud based BPM service enables to address common problems faced by traditional BPM, especially in promoting flexibility, event-driven business process to exploit opportunities in the marketplace.

What Old is New in the Large Magellanic Cloud

NASA Image and Video Library

2006-09-01

This vibrant image from NASA's Spitzer Space Telescope shows the Large Magellanic Cloud, a satellite galaxy to our own Milky Way galaxy. The infrared image, a mosaic of 300,000 individual tiles, offers astronomers a unique chance to study the lifecycle of stars and dust in a single galaxy. Nearly one million objects are revealed for the first time in this Spitzer view, which represents about a 1,000-fold improvement in sensitivity over previous space-based missions. Most of the new objects are dusty stars of various ages populating the Large Magellanic Cloud; the rest are thought to be background galaxies. The blue color in the picture, seen most prominently in the central bar, represents starlight from older stars. The chaotic, bright regions outside this bar are filled with hot, massive stars buried in thick blankets of dust. The red color around these bright regions is from dust heated by stars, while the red dots scattered throughout the picture are either dusty, old stars or more distant galaxies. The greenish clouds contain cooler interstellar gas and molecular-sized dust grains illuminated by ambient starlight. Astronomers say this image allows them to quantify the process by which space dust -- the same stuff that makes up planets and even people -- is recycled in a galaxy. The picture shows dust at its three main cosmic hangouts: around the young stars, where it is being consumed (red-tinted, bright clouds); scattered about in the space between stars (greenish clouds); and in expelled shells of material from old stars (randomly-spaced red dots). The Large Magellanic Cloud, located 160,000 light-years from Earth, is one of a handful of dwarf galaxies that orbit our own Milky Way. It is approximately one-third as wide as the Milky Way, and, if it could be seen in its entirety, would cover the same amount of sky as a grid of about 480 full moons. About one-third of the entire galaxy can be seen in the Spitzer image. This picture is a composite of infrared light captured by Spitzer. Light with wavelengths of 3.6 (blue) and 8 (green) microns was captured by the telescope's infrared array camera; 24-micron light (red) was detected by the multiband imaging photometer. http://photojournal.jpl.nasa.gov/catalog/PIA07137

Cloud condensation nuclei in Western Colorado: Observations and model predictions

NASA Astrophysics Data System (ADS)

Ward, Daniel Stewart

Variations in the warm cloud-active portion of atmospheric aerosols, or cloud condensation nuclei (CCN), have been shown to impact cloud droplet number concentration and subsequently cloud and precipitation processes. This issue carries special significance in western Colorado where a significant portion of the region's water resources is supplied by precipitation from winter season, orographic clouds, which are particularly sensitive to variations in CCN. Temporal and spatial variations in CCN in western Colorado were investigated using a combination of observations and a new method for modeling CCN. As part of the Inhibition of Snowfall by Pollution Aerosols (ISPA-III) field campaign, total particle and CCN number concentration were measured for a 24-day period in Mesa Verde National Park, climatologically upwind of the San Juan Mountains. These data were combined with CCN observations from Storm Peak Lab (SPL) in northwestern Colorado and from the King Air platform, flying north to south along the Western Slope. Altogether, the sampled aerosols were characteristic of a rural continental environment and the cloud-active portion varied slowly in time, and little in space. Estimates of the is hygroscopicity parameter indicated consistently low aerosol hygroscopicity typical of organic aerosol species. The modeling approach included the addition of prognostic CCN to the Regional Atmospheric Modeling System (RAMS). The RAMS droplet activation scheme was altered using parcel model simulations to include variations in aerosol hygroscopicity, represented by K. Analysis of the parcel model output and a supplemental sensitivity study showed that model CCN will be sensitive to changes in aerosol hygroscopicity, but only for conditions of low supersaturation or small particle sizes. Aerosol number, size distribution median radius, and hygroscopicity (represented by the K parameter) in RAMS were constrained by nudging to forecasts of these quantities from the Weather Research and Forecasting with Chemistry (WRF/Chem) model. The new system was validated against observations from SPL and research flights along the Colorado Front Range, and used to test the sensitivity of CCN in western Colorado to various anthropogenic emissions of aerosols and aerosol precursor gases. Results showed complex interactions between gas and aerosol species that could lead to an increase in CCN even when some emissions are eliminated. Both observations and modeling suggest that, although several large anthropogenic aerosol sources are located within the study region, these sources have a minor impact on the local CCN population.

Roughness Estimation from Point Clouds - A Comparison of Terrestrial Laser Scanning and Image Matching by Unmanned Aerial Vehicle Acquisitions

NASA Astrophysics Data System (ADS)

Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg

2013-04-01

Recently, terrestrial laser scanning (TLS) and matching of images acquired by unmanned arial vehicles (UAV) are operationally used for 3D geodata acquisition in Geoscience applications. However, the two systems cover different application domains in terms of acquisition conditions and data properties i.e. accuracy and line of sight. In this study we investigate the major differences between the two platforms for terrain roughness estimation. Terrain roughness is an important input for various applications such as morphometry studies, geomorphologic mapping, and natural process modeling (e.g. rockfall, avalanche, and hydraulic modeling). Data has been collected simultaneously by TLS using an Optech ILRIS3D and a rotary UAV using an octocopter from twins.nrn for a 900 m² test site located in a riverbed in Tyrol, Austria (Judenbach, Mieming). The TLS point cloud has been acquired from three scan positions. These have been registered using iterative closest point algorithm and a target-based referencing approach. For registration geometric targets (spheres) with a diameter of 20 cm were used. These targets were measured with dGPS for absolute georeferencing. The TLS point cloud has an average point density of 19,000 pts/m², which represents a point spacing of about 5 mm. 15 images where acquired by UAV in a height of 20 m using a calibrated camera with focal length of 18.3 mm. A 3D point cloud containing RGB attributes was derived using APERO/MICMAC software, by a direct georeferencing approach based on the aircraft IMU data. The point cloud is finally co-registered with the TLS data to guarantee an optimal preparation in order to perform the analysis. The UAV point cloud has an average point density of 17,500 pts/m², which represents a point spacing of 7.5 mm. After registration and georeferencing the level of detail of roughness representation in both point clouds have been compared considering elevation differences, roughness and representation of different grain sizes. UAV closes the gap between aerial and terrestrial surveys in terms of resolution and acquisition flexibility. This is also true for the data accuracy. Considering these data collection and data quality properties of both systems they have their merit on its own in terms of scale, data quality, data collection speed and application.

Investigations of cloud microphysical response to mixing using digital holography

NASA Astrophysics Data System (ADS)

Beals, Matthew Jacob

Cloud edge mixing plays an important role in the life cycle and development of clouds. Entrainment of subsaturated air affects the cloud at the microscale, altering the number density and size distribution of its droplets. The resulting effect is determined by two timescales: the time required for the mixing event to complete, and the time required for the droplets to adjust to their new environment. If mixing is rapid, evaporation of droplets is uniform and said to be homogeneous in nature. In contrast, slow mixing (compared to the adjustment timescale) results in the droplets adjusting to the transient state of the mixture, producing an inhomogeneous result. Studying this process in real clouds involves the use of airborne optical instruments capable of measuring clouds at the 'single particle' level. Single particle resolution allows for direct measurement of the droplet size distribution. This is in contrast to other 'bulk' methods (i.e. hot-wire probes, lidar, radar) which measure a higher order moment of the distribution and require assumptions about the distribution shape to compute a size distribution. The sampling strategy of current optical instruments requires them to integrate over a path tens to hundreds of meters to form a single size distribution. This is much larger than typical mixing scales (which can extend down to the order of centimeters), resulting in difficulties resolving mixing signatures. The Holodec is an optical particle instrument that uses digital holography to record discrete, local volumes of droplets. This method allows for statistically significant size distributions to be calculated for centimeter scale volumes, allowing for full resolution at the scales important to the mixing process. The hologram also records the three dimensional position of all particles within the volume, allowing for the spatial structure of the cloud volume to be studied. Both of these features represent a new and unique view into the mixing problem. In this dissertation, holographic data recorded during two different field projects is analyzed to study the mixing structure of cumulus clouds. Using Holodec data, it is shown that mixing at cloud top can produce regions of clear but humid air that can subside down along the edge of the cloud as a narrow shell, or advect down shear as a 'humid halo'. This air is then entrained into the cloud at lower levels, producing mixing that appears to be very inhomogeneous. This inhomogeneous-like mixing is shown to be well correlated with regions containing elevated concentrations of large droplets. This is used to argue in favor of the hypothesis that dilution can lead to enhanced droplet growth rates. I also make observations on the microscale spatial structure of observed cloud volumes recorded by the Holodec.

Alterations of Cloud Microphysics Due to Cloud Processed CCN

NASA Astrophysics Data System (ADS)

Hudson, J. G.; Tabor, S. S.; Noble, S. R., Jr.

2015-12-01

High-resolution CCN spectra have revealed bimodality (Hudson et al. 2015) similar to aerosol size spectra (e.g., Hoppel et al. 1985). Bimodality is caused by chemical and physical cloud processes that increase mass or hygroscopicity of only CCN that produced activated cloud droplets. Bimodality is categorized by relative CCN concentrations (NCCN) within the two modes, Nu-Np; i.e., NCCN within the higher critical supersaturation, Sc, mode that did not undergo cloud processing minus NCCN within the lower Sc mode that was cloud processed. Lower, especially negative, Nu-Np designates greater processing. The table shows regressions between Nu-Np and characteristics of clouds nearest the CCN measurements. ICE-T MASE parameter R SL R SL Nc 0.17 93.24 -0.26 98.65 MD -0.31 99.69 0.33 99.78 σ -0.27 99.04 0.48 100.00 Ld -0.31 99.61 0.38 99.96 Table. Correlation coefficients, R, and one-tailed significance levels in percent, SL, for Nu-Np with microphysics of the clouds closest to each CCN measurement, 75 ICE-T and 74 MASE cases. Nc is cloud droplet concentration, MD is cloud droplet mean diameter, σ is standard deviation of cloud droplet spectra, Ldis drizzle drop LWC. Two aircraft field campaigns, Ice in Clouds Experiment-Tropical (ICE-T) and Marine Stratus/Stratocumulus Experiment (MASE) show opposite R signs because coalescence dominated cloud processing in low altitude ICE-T cumuli whereas chemical transformations predominated in MASE low altitude polluted stratus. Coalescence reduces Nc and NCCN, which thus increases MD, and σ, which promote Ld. Chemical transformations, e.g., SO2 to SO4, increase CCN hygroscopicity, thus reducing Sc, but not affecting Nc or NCCN. Lower Sc CCN are capable of producing greater Nc in subsequent cloud cycles, which leads to lower MD and σ which reduce Ld (figure). These observations are consistent with cloud droplet growth models for the higher vertical wind (W) of cumuli and lower W of stratus. Coalescence thus reduces the indirect aerosol effect (IAE) with a positive feedback that further enhances coalescence and drizzle. Chemical cloud processing enhances both components of IAE; 1st IAE by greater droplet surface area, 2ndIAE by suppressing drizzle and thus increasing cloudiness. Hoppel, Fitzgerald and Larson: JGR 90, 2365-79 Hudson, Noble and Tabor: JGRA 120, 3436-52

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2002-01-01

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). The 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 (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and incoming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a cloud-resolving model, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. Dr. Joanne Simpson played a central role in GCE modeling developments and applications. She was the lead author or co-author on more than forty GCE modeling papers. In this paper, a brief discussion and review of the application of the GCE model to (1) cloud interactions and mergers, (2) convective and stratiform interaction, (3) mechanisms of cloud-radiation interaction, (4) latent heating profiles and TRMM, and (5) responses of cloud systems to large-scale processes are provided. Comparisons between the GCE model's results, other cloud-resolving model results and observations are also examined.

Education, Outreach, and Diversity Partnerships and Science Education Resources From the Center for Multi-scale Modeling of Atmospheric Processes

NASA Astrophysics Data System (ADS)

Foster, S. Q.; Randall, D.; Denning, S.; Jones, B.; Russell, R.; Gardiner, L.; Hatheway, B.; Johnson, R. M.; Drossman, H.; Pandya, R.; Swartz, D.; Lanting, J.; Pitot, L.

2007-12-01

The need for improving the representation of cloud processes in climate models has been one of the most important limitations of the reliability of climate-change simulations. The new National Science Foundation- funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University (CSU) is a major research program addressing this problem over the next five years through a revolutionary new approach to representing cloud processes on their native scales, including the cloud-scale interactions among the many physical and chemical processes that are active in cloud systems. At the end of its first year, CMMAP has established effective partnerships between scientists, students, and teachers to meet its goals to: (1) provide first-rate graduate education in atmospheric science; (2) recruit diverse undergraduates into graduate education and careers in climate science; and (3) develop, evaluate, and disseminate educational resources designed to inform K-12 students, teachers, and the general public about the nature of the climate system, global climate change, and career opportunities in climate science. This presentation will describe the partners, our challenges and successes, and measures of achievement involved in the integrated suite of programs launched in the first year. They include: (1) a new high school Colorado Climate Conference drawing prestigious climate scientists to speak to students, (2) a summer Weather and Climate Workshop at CSU and the National Center for Atmospheric Research introducing K-12 teachers to Earth system science and a rich toolkit of teaching materials, (3) a program from CSU's Little Shop of Physics reaching 50 schools and 20,000 K-12 students through the new "It's Up In the Air" program, (4) expanded content, imagery, and interactives on clouds, weather, climate, and modeling for students, teachers, and the public on The Windows to the Universe web site at University Corporation for Atmospheric Research (UCAR), (5) mentoring programs engaging diverse undergraduate and graduate level students in CMMAP research through UCAR's Significant Opportunities in Atmospheric Research and Science (SOARS) Program, and (6) after school activities about clouds, climate and weather for underrepresented middle school students at the Catamount Institute. CMMAP is also enabling Windows to the Universe to continue its commitment to translate all new web pages into Spanish. This presentation will explain how resources emerging from CMMAP can be accessed and used by the entire Earth and Ocean Science educational outreach community.

Clouds, weather, climate, and modeling for K-12 and public audiences from the Center for Multi-scale Modeling of Atmospheric Processes

NASA Astrophysics Data System (ADS)

Foster, S. Q.; Johnson, R. M.; Randall, D. A.; Denning, A.; Russell, R. M.; Gardiner, L. S.; Hatheway, B.; Jones, B.; Burt, M. A.; Genyuk, J.

2010-12-01

The need for improving the representation of cloud processes in climate models has been one of the most important limitations of the reliability of climate-change simulations. Now in its fifth year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University (CSU) is addressing this problem through a revolutionary new approach to representing cloud processes on their native scales, including the cloud-scale interaction processes that are active in cloud systems. CMMAP has set ambitious education and human-resource goals to share basic information about the atmosphere, clouds, weather, climate, and modeling with diverse K-12 and public audiences. This is accomplished through collaborations in resource development and dissemination between CMMAP scientists, CSU’s Little Shop of Physics (LSOP) program, and the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). Little Shop of Physics develops new hands on science activities demonstrating basic science concepts fundamental to understanding atmospheric characteristics, weather, and climate. Videos capture demonstrations of children completing these activities which are broadcast to school districts and public television programs. CMMAP and LSOP educators and scientists partner in teaching a summer professional development workshops for teachers at CSU with a semester's worth of college-level content on the basic physics of the atmosphere, weather, climate, climate modeling, and climate change, as well as dozens of LSOP inquiry-based activities suitable for use in classrooms. The W2U project complements these efforts by developing and broadly disseminating new CMMAP-related online content pages, animations, interactives, image galleries, scientists’ biographies, and LSOP videos to K-12 and public audiences. Reaching nearly 20 million users annually, W2U is highly valued as a curriculum enhancement resource, because its content is written at three levels in English and Spanish. Links between science topics and literature, art, and mythology enable teachers of English Language Learners, literacy, and the arts to integrate science into their classrooms. In summary, the CMMAP NSF-funded Science and Technology Center has established a highly effective and productive partnership of scientists and educators focused on enhancing public science literacy about weather, climate, and global change. All CMMAP, LSOP, and W2U resources can be accessed online at no cost by the entire atmospheric science K-12 and informal science education community.

Insights on How NASA's Earth Observing System (EOS) Monitors Our World Environment

NASA Technical Reports Server (NTRS)

King, Michael D.

2000-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, four EOS science missions were launched, representing observations of (1) total solar irradiance, (2) Earth radiation budget, (3) land cover and land use change, (4) ocean processes (vector wind, sea surface temperature, and ocean color), (5) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (6) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists are using EOS data to examine land use and natural hazards, environmental air quality, including dust storms over the world's deserts, cloud and radiation properties, sea surface temperature, and winds over the ocean.

Physical and chemical properties of ice residuals during the 2013 and 2014 CLACE campaigns

NASA Astrophysics Data System (ADS)

Kupiszewski, Piotr; Weingartner, Ernest; Vochezer, Paul; Hammer, Emanuel; Gysel, Martin; Färber, Raphael; Fuchs, Claudia; Schnaiter, Martin; Baltensperger, Urs; Schmidt, Susan; Schneider, Johannes; Bigi, Alessandro; Toprak, Emre; Linke, Claudia; Klimach, Thomas

2014-05-01

The shortcomings in our understanding and, thus, representation of aerosol-cloud interactions are one of the major sources of uncertainty in climate model projections. Among the poorly understood processes is mixed-phase cloud formation via heterogeneous nucleation, and the subsequent spatial and temporal evolution of such clouds. Cloud glaciation augments precipitation formation, resulting in decreased cloud cover and lifetime, and affects cloud radiative properties. Meanwhile, the physical and chemical properties of atmospherically relevant ice nuclei (IN), the sub-population of aerosol particles which enable heterogeneous nucleation, are not well known. Extraction of ice residuals (IR) in mixed-phase clouds is a difficult task, requiring separation of the few small, freshly formed ice crystals (the IR within such crystals can be deemed representative of the original IN) not only from interstitial particles, but also from the numerous supercooled droplets which have aerodynamic diameters similar to those of the ice crystals. In order to address the difficulties with ice crystal sampling and IR extraction in mixed-phase clouds, the new Ice Selective Inlet (ISI) has been designed and deployed at the Jungfraujoch field site. Small ice crystals are selectively sampled via the inlet with simultaneous counting, sizing and imaging of hydrometeors contained in the cloud by a set of optical particle spectrometers, namely Welas optical particle counters (OPC) and a Particle Phase Discriminator (PPD). The heart of the ISI is a droplet evaporation unit with ice-covered inner walls, resulting in removal of droplets using the Wegener-Bergeron-Findeisen process, while transmitting a relatively high fraction of small ice crystals. The ISI was deployed in the winters of 2013 and 2014 at the high alpine Jungfraujoch site (3580 m.a.s.l) during the intensive CLACE field campaigns. The measurements focused on analysis of the physical and chemical characteristics of IR and the microphysical properties of mixed-phase clouds. A host of aerosol instrumentation was deployed downstream of the ISI, including a Grimm OPC and a scanning mobility particle sizer (SMPS) for number size distribution measurements, as well as a single particle mass spectrometer (ALABAMA; 2013 only), single particle soot photometers (SP2) and a Wideband Integrated Bioaerosol Sensor (WIBS-4) for analysis of the chemical composition, with particular focus on the content of black carbon (BC) and biological particles in IR. Corresponding instrumentation sampled through a total aerosol inlet. By comparing observations from the ISI with those from the total inlet the characteristics of ice residuals relative to the total aerosol could be established. First results from these analyses will be presented.

The Goddard Cumulus Ensemble Model (GCE): Improvements and Applications for Studying Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, Stephen E.; Zeng, Xiping; Li, Xiaowen; Matsui, Toshi; Mohr, Karen; Posselt, Derek; Chern, Jiundar; Peters-Lidard, Christa; Norris, Peter M.;

Microphysical Properties and Water Budget for Summer Convective Clouds over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Guo, X.; Tang, J.; Chang, Y.

2017-12-01

During the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III), the clouds and precipitation processes over the Tibetan Plateau have been intensively investigated. On basis of field campaign, the cloud microphysical structure, water transformation and budget properties for typical convective precipitation processes in the summer season of 2014 over the plateau are studied using mesoscale numerical prediction model (WRF) combined with observational data collected during the experiment. The results indicate that WRF model could reproduce the general characteristics of diurnal variation of clouds and precipitation process over the plateau, however, the temporal and spatial distribution and intensity of cloud bands and precipitation simulated by WRF model still had large differences with those observed. Ice process played a critical role in the development of summer convective clouds and precipitation over the plateau. The surface precipitation was primarily formed by the melting process of graupel particles. Although the warm cloud microphysical process had small direct contribution on the surface precipitation, it had an important contribution in the formation of graupel embryos. High amount of supercooled cloud water content and graupel particles could be found in the clouds. The formation and growth of snow particles relied on the conversion of ice crystal and the aggregation with ice crystal over 12 km (-40°), but the formation of snow particles below 12 km (-40°)was dependent on the conversion of Bergeron process of ice crystals and its growth resulted from riming process with supercooled cloud water. The accretion process of supercooled raindrops by ice crystal and snow particles contributed to the production of graupel embryos and their growth mainly relied on the riming process with supercooled cloud water and aggregation process with snow particles. The mean daily conversion rate from vapor to precipitation was as high as 27.27%, which is close to Yangtze River downstream, and is higher than the regions of northern and northwestern China. The contribution of daily mean surface evaporation to precipitation was 10.92%, indicating that the 90% rainfall was from the conversion of water vapor outside the plateau.

Nowcasting Cloud Fields for U.S. Air Force Special Operations

DTIC Science & Technology

2017-03-01

application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES

Relationships Between Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes on Intraseasonal Time Scales

NASA Technical Reports Server (NTRS)

Ramey, Holly S.; Robertson, Franklin R.

2009-01-01

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20oN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Relationships Between Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes on Intraseasonal Time Scales

NASA Technical Reports Server (NTRS)

Ramey, Holly S.; Robertson, Franklin R.

2010-01-01

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20degN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Dynamics, thermodynamics, radiation, and cloudiness associated with cumulus-topped marine boundary layers

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

Ghate, Virendra P.; Miller, Mark

The overall goal of this project was to improve the understanding of marine boundary clouds by using data collected at the Atmospheric Radiation Measurement (ARM) sites, so that they can be better represented in global climate models (GCMs). Marine boundary clouds are observed regularly over the tropical and subtropical oceans. They are an important element of the Earth’s climate system because they have substantial impact on the radiation budget together with the boundary layer moisture, and energy transports. These clouds also have an impact on large-scale precipitation features like the Inter Tropical Convergence Zone (ITCZ). Because these clouds occur atmore » temporal and spatial scales much smaller than those relevant to GCMs, their effects and the associated processes need to be parameterized in GCM simulations aimed at predicting future climate and energy needs. Specifically, this project’s objectives were to (1) characterize the surface turbulent fluxes, boundary layer thermodynamics, radiation field, and cloudiness associated with cumulus-topped marine boundary layers; (2) explore the similarities and differences in cloudiness and boundary layer conditions observed in the tropical and trade-wind regions; and (3) understand similarities and differences by using a simple bulk boundary layer model. In addition to working toward achieving the project’s three objectives, we also worked on understanding the role played by different forcing mechanisms in maintaining turbulence within cloud-topped boundary layers We focused our research on stratocumulus clouds during the first phase of the project, and cumulus clouds during the rest of the project. Below is a brief description of manuscripts published in peer-reviewed journals that describe results from our analyses.« less

Examining the Impact of Smoke on Frontal Clouds and Precipitation During the 2002 Yakutsk Wildfires Using the WRF-Chem-SMOKE Model and Satellite Data

NASA Astrophysics Data System (ADS)

Lu, Zheng; Sokolik, Irina N.

2017-12-01

In 2002, an enormous amount of smoke has been emitted from Yakutsk wildfires. In this study, we examine the impact of smoke on cloud properties and precipitation associated with frontal systems using the WRF-Chem-SMOKE model and satellite data. The smoke emissions are computed using the fire radiative power technique. Smoke particles are represented as an internal mixture of organic matter (OM), black carbon (BC), and other inorganic matter, and their microphysical and radiative effects are explicitly modeled. After examining the fire activities, we identified two fire periods (FP1 and FP2). During FP1, in the cloud deck with the high cloud droplet number concentration (CDNC), but the relatively small amount of ice nuclei (IN), the rain and snow water contents (RWC and SWC) were strongly reduced, because of suppressed collision-coalescence and riming processes. The cloud cells acquired the longer lifetime and traveled farther downwind. During FP2, in the cloud deck with relatively high CDNC and IN, RWC was reduced; however, the large amounts of IN triggered the glaciation indirect effect and leaded to increased SWC. Due to the competing effects of CDNC and IN, changes in the cloud lifetime were small. Consequently, smoke-induced changes in the total cloudiness cause a dipole feature. After the smoke was nearly consumed during FP1, the large-scale dynamics of the frontal system was altered by smoke. The onset of the precipitation was delayed by 1 day. In FP2, the onset of the precipitation was not delayed but occurred at different locations, and the area-averaged precipitation was slightly reduced ( 0.5 mm/day).

Intraseasonal Variations in Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes

NASA Technical Reports Server (NTRS)

Ramey, Holly S.; Robertson, Franklin R.

2009-01-01

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20oN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

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.

Modeling the Evolution of Disk Galaxies. I. The Chemodynamical Method and the Galaxy Model

NASA Astrophysics Data System (ADS)

Samland, M.; Hensler, G.; Theis, Ch.

1997-02-01

Here we present our two-dimensional chemodynamical code CoDEx, which we developed for the purpose of modeling the evolution of galaxies in a self-consistent manner. The code solves the hydrodynamical and momentum equations for three stellar components and the multiphase interstellar medium (clouds and intercloud medium), including star formation, Type I and Type II supernovae, planetary nebulae, stellar winds, evaporation and condensation, drag, cloud collisions, heating and cooling, and stellar nucleosynthesis. These processes are treated simultaneously, coupling a large range in temporal and spatial scales, to account for feedback and self-regulation processes, which play an extraordinarily important role in the galactic evolution. The evolution of galaxies of different masses and angular momenta is followed through all stages from the initial protogalactic clouds until now. In this first paper we present a representative model of the Milky Way and compare it with observations. The capability of chemodynamical models is convincingly proved by the excellent agreement with various observations. In addition, well-known problems (the G-dwarf problem, the discrepancy between local effective yields, etc.), which so far could be only explained by artificial constraints, are also solved in the global scenario. Starting from a rotating protogalactic gas cloud in virial equilibrium, which collapses owing to dissipative cloud-cloud collisions, we can follow the galactic evolution in detail. Owing to the collapse, the gas density increases, stars are forming, and the first Type II supernovae explode. The collapse time is 1 order of magnitude longer than the dynamical free-fall time because of the energy release by Type II supernovae. The supernovae also drive hot metal-rich gas ejected from massive stars into the halo, and as a consequence, the clouds in the star-forming regions have lower metallicities than the clouds in the halo. The observed negative metallicity gradients do not form before t = 6 × 109 yr. These outward gas flows prevent any clear correlation between local star formation rate and enrichment and also prevent a unique age-metallicity relation. The situation, however, is even more complicated, because the mass return of intermediate-mass stars (Type I supernovae and planetary nebulae) is delayed depending on the type of precursor. Since our chemodynamical model includes all these processes, we can calculate, e.g., the [O/H] distribution of stars and find good agreement everywhere in bulge, disk, and halo. From the galactic oxygen to iron ratio, we can determine the supernovae ([II + Ib]/Ia) ratio for different types of Type Ia supernovae (such as carbon deflagration or sub-Chandrasekhar models) and find that the ratio should be in the range 1.0-3.8. The chemodynamical model also traces other chemical elements (e.g., N + C), density distributions, gas flows, velocity dispersions of the stars and clouds, star formation, planetary nebula rates, cloud collision, condensation and evaporation rates, and the cooling due to radiation. The chemodynamical treatment of galaxy evolution should be envisaged as a necessary development, which takes those processes into account that affect the dynamical, energetical, and chemical evolution.

The Structure and Evolution of Self-Gravitating Molecular Clouds

NASA Astrophysics Data System (ADS)

Holliman, John Herbert, II

1995-01-01

We present a theoretical formalism to evaluate the structure of molecular clouds and to determine precollapse conditions in star-forming regions. Models consist of pressure-bounded, self-gravitating spheres of a single -fluid ideal gas. We treat the case without rotation. The analysis is generalized to consider states in hydrostatic equilibrium maintained by multiple pressure components. Individual pressures vary with density as P_i(r) ~ rho^{gamma {rm p},i}(r), where gamma_{rm p},i is the polytropic index. Evolution depends additionally on whether conduction occurs on a dynamical time scale and on the adiabatic index gammai of each component, which is modified to account for the effects of any thermal coupling to the environment of the cloud. Special attention is given to properly representing the major contributors to dynamical support in molecular clouds: the pressures due to static magnetic fields, Alfven waves, and thermal motions. Straightforward adjustments to the model allow us to treat the intrinsically anisotropic support provided by the static fields. We derive structure equations, as well as perturbation equations for performing a linear stability analysis. The analysis provides insight on the nature of dynamical motions due to collapse from an equilibrium state and estimates the mass of condensed objects that form in such a process. After presenting a set of general results, we describe models of star-forming regions that include the major pressure components. We parameterize the extent of ambipolar diffusion. The analysis contributes to the physical understanding of several key results from observations of these regions. Commonly observed quantities are explicitly cross-referenced with model results. We theoretically determine density and linewidth profiles on scales ranging from that of molecular cloud cores to that of giant molecular clouds (GMCs). The model offers an explanation of the mean pressures in GMCs, which are observed to be high relative to that in the intercloud medium. We estimate what fraction of a cloud on the verge of gravitational collapse will ultimately form a condensed object, and we predict the qualitative appearance of the collapse. Finally, we simulate fragmentation--a key step in the star-forming process whereby molecular clouds or clumps within more massive clouds break up into substantially less massive cores that can in turn condense into stars. Fragmentation occurs in the context of dynamical collapse--a highly nonlinear process--so it has been difficult to reach a consensus on its specific appearance or on the influence of initial conditions. Increases in density by several orders of magnitude and the unknown, time-dependent positions of the rapidly evolving fragments present difficulties for the simulation of fragmentation. In order to increase the efficiency and effective resolution with which we can model this process, we have assembled can adaptive mesh refinement (AMR) hydrodynamics algorithm and an adaptive elliptical solver for self-gravity. The code is adaptive in the sense that it can dynamically and automatically alter the configuration of a recursively finer mesh in the computational domain. A test suite helps confirm the proper operation of the algorithm. Using initial conditions adopted in previous fragmentation studies, we simulate the collapse of a molecular cloud core. (Abstract shortened by UMI.).

On The Cloud Processing of Aerosol Particles: An Entraining Air Parcel Model With Two-dimensional Spectral Cloud Microphysics and A New Formulation of The Collection Kernel

NASA Astrophysics Data System (ADS)

Bott, Andreas; Kerkweg, Astrid; Wurzler, Sabine

A study has been made of the modification of aerosol spectra due to cloud pro- cesses and the impact of the modified aerosols on the microphysical structure of future clouds. For this purpose an entraining air parcel model with two-dimensional spectral cloud microphysics has been used. In order to treat collision/coalescence processes in the two-dimensional microphysical module, a new realistic and continuous formu- lation of the collection kernel has been developed. Based on experimental data, the kernel covers the entire investigated size range of aerosols, cloud and rain drops, that is the kernel combines all important coalescence processes such as the collision of cloud drops as well as the impaction scavenging of small aerosols by big raindrops. Since chemical reactions in the gas phase and in cloud drops have an important impact on the physico-chemical properties of aerosol particles, the parcel model has been extended by a chemical module describing gas phase and aqueous phase chemical reactions. However, it will be shown that in the numerical case studies presented in this paper the modification of aerosols by chemical reactions has a minor influence on the microphysical structure of future clouds. The major process yielding in a second cloud event an enhanced formation of rain is the production of large aerosol particles by collision/coalescence processes in the first cloud.

Climate simulations and projections with a super-parameterized climate model

DOE PAGES

Stan, Cristiana; Xu, Li

2014-07-01

The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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 cloud drops which is reduced in number and almost devoid of large particles. Consequently, impaction scavenging can probably be neglected inside clouds. Below clouds, impaction scavenging contributes around 30% to the particle mass reaching the ground by a rainfall event. The exact amount depends on the precise case studied. Nucleation and impaction scavenging directly by the ice phase in mixed phase clouds seems to play a minor role with respect to the particle mass that enters the ice particles via freezing of the liquid phase.The aerosol scavenging efficiency generally follows rather closely the precipitation scavenging value. The nucleation scavenging efficiency is around 90% for the liquid phase clouds and impaction scavenging generally contributed to about 30% of the particle mass in the rain. Clouds are very efficient in pumping up the boundary layer aerosol which essentially determines the cloud properties. For a marine case studied the net pumping depleted about 70% of the aerosol from the section of the boundary layer considered. The larger particles (and thus 70% of the mass vented up) got activated inside the cloud. A weak net import through cloud top and the upwind side was found, as well as a larger net export at the downwind side. The outside cloud subsidence can add to the replenishment of the boundary layer and eventually cause a recycling of the particles into the cloud. The results of the parcel model studies seem to indicate that increasing particulate pollution and decreasing solubility suppresses rain formation. In individual and short time cloud simulations this behaviour was even confirmed in our 3D model studies. However, taking into account entire cloud fields over longer periods of time yields the strong spatial and temporal variability of the results with isolated regions of inverse correlation of the effects. Even though in general initially the expected behaviour was found, after several hours of simulation, the overall precipitation amounts of the more polluted cases caught up. This suggests that a changing pollution will affect the spatial and temporal pattern of precipitation, but will probably not reduce the overall long term precipitation amount which might be entirely governed by the moisture state of the atmosphere. Our results regarding mixed phase precipitation with respect to "all liquid" cases seem to confirm this idea, as with increasing modelling time the precipitation mass of both cases also become similar.

An Automatic Method for Geometric Segmentation of Masonry Arch Bridges for Structural Engineering Purposes

NASA Astrophysics Data System (ADS)

Riveiro, B.; DeJong, M.; Conde, B.

2016-06-01

Despite the tremendous advantages of the laser scanning technology for the geometric characterization of built constructions, there are important limitations preventing more widespread implementation in the structural engineering domain. Even though the technology provides extensive and accurate information to perform structural assessment and health monitoring, many people are resistant to the technology due to the processing times involved. Thus, new methods that can automatically process LiDAR data and subsequently provide an automatic and organized interpretation are required. This paper presents a new method for fully automated point cloud segmentation of masonry arch bridges. The method efficiently creates segmented, spatially related and organized point clouds, which each contain the relevant geometric data for a particular component (pier, arch, spandrel wall, etc.) of the structure. The segmentation procedure comprises a heuristic approach for the separation of different vertical walls, and later image processing tools adapted to voxel structures allows the efficient segmentation of the main structural elements of the bridge. The proposed methodology provides the essential processed data required for structural assessment of masonry arch bridges based on geometric anomalies. The method is validated using a representative sample of masonry arch bridges in Spain.

Microbiome of the upper troposphere: Species composition and prevalence, effects of tropical storms, and atmospheric implications

PubMed Central

DeLeon-Rodriguez, Natasha; Lathem, Terry L.; Rodriguez-R, Luis M.; Barazesh, James M.; Anderson, Bruce E.; Beyersdorf, Andreas J.; Ziemba, Luke D.; Bergin, Michael; Nenes, Athanasios; Konstantinidis, Konstantinos T.

2013-01-01

The composition and prevalence of microorganisms in the middle-to-upper troposphere (8–15 km altitude) and their role in aerosol-cloud-precipitation interactions represent important, unresolved questions for biological and atmospheric science. In particular, airborne microorganisms above the oceans remain essentially uncharacterized, as most work to date is restricted to samples taken near the Earth’s surface. Here we report on the microbiome of low- and high-altitude air masses sampled onboard the National Aeronautics and Space Administration DC-8 platform during the 2010 Genesis and Rapid Intensification Processes campaign in the Caribbean Sea. The samples were collected in cloudy and cloud-free air masses before, during, and after two major tropical hurricanes, Earl and Karl. Quantitative PCR and microscopy revealed that viable bacterial cells represented on average around 20% of the total particles in the 0.25- to 1-μm diameter range and were at least an order of magnitude more abundant than fungal cells, suggesting that bacteria represent an important and underestimated fraction of micrometer-sized atmospheric aerosols. The samples from the two hurricanes were characterized by significantly different bacterial communities, revealing that hurricanes aerosolize a large amount of new cells. Nonetheless, 17 bacterial taxa, including taxa that are known to use C1–C4 carbon compounds present in the atmosphere, were found in all samples, indicating that these organisms possess traits that allow survival in the troposphere. The findings presented here suggest that the microbiome is a dynamic and underappreciated aspect of the upper troposphere with potentially important impacts on the hydrological cycle, clouds, and climate. PMID:23359712

Study of the transport parameters of cloud lightning plasmas

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

Chang, Z. S.; Yuan, P.; Zhao, N.

2010-11-15

Three spectra of cloud lightning have been acquired in Tibet (China) using a slitless grating spectrograph. The electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity of the cloud lightning, for the first time, are calculated by applying the transport theory of air plasma. In addition, we investigate the change behaviors of parameters (the temperature, the electron density, the electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity) in one of the cloud lightning channels. The result shows that these parameters decrease slightly along developing direction of the cloud lightning channel. Moreover, they represent similar suddenmore » change behavior in tortuous positions and the branch of the cloud lightning channel.« less

Why do global climate models struggle to represent low-level clouds in the West African summer monsoon?

NASA Astrophysics Data System (ADS)

Knippertz, Peter; Hannak, Lisa; Fink, Andreas H.; Kniffka, Anke; Pante, Gregor

2017-04-01

Climate models struggle to realistically represent the West African monsoon (WAM), which hinders reliable future projections and the development of adequate adaption measures. Low-level clouds over southern West Africa (5-10°N, 8°W-8°E) during July-September are an integral part of the WAM through their effect on the surface energy balance and precipitation, but their representation in climate models has so far received little attention. These clouds usually form during the night near the level of the nocturnal low-level jet ( 950 hPa), thicken and spread until the mid-morning ( 09 UTC), and then break up and rise in the course of the day, typically to about 850 hPa. The low thermal contrast to the surface and the frequent presence of obscuring higher-level clouds make detection of the low-level clouds from space rather challenging. Here we use 30 years of output from 18 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) as well as 20 years of output from 8 models participating in the Year of Tropical Convection (YoTC) experiments to identify cloud biases and their causes. A great advantage of the YoTC dataset is the 6-hourly output frequency, which allows an analysis of the diurnal cycle, and the availability of temperature and moisture tendencies from parameterized processes such as convection, radiation and boundary-layer turbulence. A comparison to earlier analyses based on CMIP3 output reveals rather limited improvements with regard to the represenation of low-level cloud and winds. Compared to ERA-Interim re-analyses, which shows satisfactory agreement with surface observations, many of the CMIP5 and YoTC models still have large biases in low-level cloudiness of both signs and a tendency to too high elevation and too weak diurnal cycles. At the same time, these models tend to have too strong low-level jets, the impact of which is unclear due to concomitant effects on temperature and moisture advection as well as turbulent mixing. Part of the differences between the models and ERA-Interim appear to be related to the different subgrid cloud schemes used. While nighttime tendencies in temperature and humidity are broadly realistic in most models, daytime tendencies show large variation in the vertical transport of heat and moisture. Many models simulate too low near-surface relative humidities, leading to insufficient low cloud cover, abundant solar radiation, and thus a too large diurnal cycle in temperature and relative humidity. Currently, targeted model sensitivity experiments are conducted to test possible feedback mechanisms between low clouds, radiation, boundary-layer dynamics, precipitation and the WAM circulation in the framework of the EU-funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project (http://www.dacciwa.eu).

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Simpson, J.; Baker, D.; Braun, S.; Chou, M.-D.; Ferrier, B.; Johnson, D.; Khain, A.; Lang, S.; Lynn, B.

2001-01-01

The response of cloud systems to their environment is an important link in a chain of processes responsible for monsoons, frontal depression, El Nino Southern Oscillation (ENSO) episodes and other climate variations (e.g., 30-60 day intra-seasonal oscillations). Numerical models of cloud properties provide essential insights into the interactions of clouds with each other, with their surroundings, and with land and ocean surfaces. Significant advances are currently being made in the modeling of rainfall and rain-related cloud processes, ranging in scales from the very small up to the simulation of an extensive population of raining cumulus clouds in a tropical- or midlatitude-storm environment. The Goddard Cumulus Ensemble (GCE) model is a multi-dimensional nonhydrostatic dynamic/microphysical cloud resolving model. It has been used to simulate many different mesoscale convective systems that occurred in various geographic locations. In this paper, recent GCE model improvements (microphysics, radiation and surface processes) will be described as well as their impact on the development of precipitation events from various geographic locations. The performance of these new physical processes will be examined by comparing the model results with observations. In addition, the explicit interactive processes between cloud, radiation and surface processes will be discussed.

Modeling Studying the Role of Bacteria on ice Nucleation Processes

NASA Astrophysics Data System (ADS)

Sun, J.

2006-12-01

Certain air-borne bacteria have been recognized as active ice nuclei at the temperatures warm than - 10°C. Ice nucleating bacteria commonly found in plants and ocean surface. These ice nucleating bacteria are readily disseminated into the atmosphere and have been observed in clouds and hailstones, and their importance in cloud formation process and precipitation, as well as causing diseases in plants and animal kingdom, have been considered for over two decades, but their significance in atmospheric processes are yet to be understood. A 1.5-D non-hydrostatic cumulus cloud model with bin-resolved microphysics is developed and is to used to examine the relative importance of sulphate aerosol concentrations on the evolution of cumulus cloud droplet spectra and ice multiplication process, as well as ice initiation process by ice nucleating bacteria in the growing stage of cumulus clouds and the key role of this process on the ice multiplication in the subsequent dissipating stage of cumulus clouds. In this paper, we will present some sensitivity test results of the evolution of cumulus cloud spectra, ice concentrations at various concentrations of sulfate aerosols, and at different ideal sounding profiles. We will discuss the implication of our results in understanding of ice nucleation processes.

Formation of compact HII regions possibly triggered by cloud-cloud collision

NASA Astrophysics Data System (ADS)

Ohama, Akio; Torii, Kazufumi; Hasegawa, Keisuke; Fukui, Yasuo

2015-08-01

Compact HII regions are ionized by young high-mass star(s) and ~1000 compact HII regions are cataloged in the Galaxy (Urquhart et al. MNRAS 443, 1555-1586 (2014)). Compact HII regions are one of the major populations of Galactic HII regions. The molecular environments around compact HII regions are however not well understood due to lack of extensive molecular surveys. In order to better understand formation of exciting stars and compact HII regions, we have carried out a systematic study of molecular clouds toward compact HII regions by using the 12CO datasets obtained with the JCMT and NANTEN2 telescopes for l = 10 - 56, and present here the first results.In one of the present samples, RCW166, we have discovered that the HII region is associated with two molecular clouds whose velocity separation is ~10 km s-1 the two clouds show complimentary spatial distributions, where one of the clouds have a cavity-like distribution apparently embracing the other. We present an interpretation that the two clouds collided with each other and the cavity-like distribution represents a hole created by the collision in the larger cloud as modeled by Habe and Ohta (1992). Similar molecular distributions are often found in the other compact HII regions in the present study.A recent study by Torii et al. (2015, arXiv:1503.00070) indicates that the Spitzer bubble RCW120 was formed by cloud-cloud collision where the inside of the cavity is fully ionized by the exiting stars. RCW166, on the other hand, shows that only a small part of the cavity, the compact HII region, is ionized. We thus suggest that RCW166 represents an evolutionary stage corresponding to an earlier phase of RCW120 in the collision scenario.

Superposition and alignment of labeled point clouds.

PubMed

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

2011-01-01

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

Multimodel evaluation of cloud phase transition using satellite and reanalysis data

NASA Astrophysics Data System (ADS)

Cesana, G.; Waliser, D. E.; Jiang, X.; Li, J.-L. F.

2015-08-01

We take advantage of climate simulations from two multimodel experiments to characterize and evaluate the cloud phase partitioning in 16 general circulation models (GCMs), specifically the vertical structure of the transition between liquid and ice in clouds. We base our analysis on the ratio of ice condensates to the total condensates (phase ratio, PR). Its transition at 90% (PR90) and its links with other relevant variables are evaluated using the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation Cloud Product climatology, reanalysis data, and other satellite observations. In 13 of 16 models, the PR90 transition height occurs too low (6 km to 8.4 km) and at temperatures too warm (-13.9°C to -32.5°C) compared to observations (8.6 km, -33.7°C); features consistent with a lack of supercooled liquid with respect to ice above 6.5 km. However, this bias would be slightly reduced by using the lidar simulator. In convective regimes (more humid air and precipitation), the observed cloud phase transition occurs at a warmer temperature than for subsidence regimes (less humid air and precipitation). Only few models manage to roughly replicate the observed correlations with humidity (5/16), vertical velocity (5/16), and precipitation (4/16); 3/16 perform well for all these parameters (MPI-ESM, NCAR-CAM5, and NCHU). Using an observation-based Clausius-Clapeyron phase diagram, we illustrate that the Bergeron-Findeisen process is a necessary condition for models to represent the observed features. Finally, the best models are those that include more complex microphysics.

Nighttime lidar water vapor mixing ratio profiling over Warsaw - impact of the relative humidity profile on cloud formation

NASA Astrophysics Data System (ADS)

Costa Surós, Montserrat; Stachlewska, Iwona S.

2016-04-01

A long-term study, assessing ground-based remote Raman lidar versus in-situ radiosounding has been conducted with the aim of improving the knowledge on the water content vertical profile through the atmosphere, and thus the conditions for cloud formation processes. Water vapor mixing ratio (WVMR) and relative humidity (RH) profiles were retrieved from ADR Lidar (PollyXT-type, EARLINET site in Warsaw). So far, more than 100 nighttime profiles averaged over 1h around midnight from July 2013 to December 2015 have been investigated. Data were evaluated with molecular extinctions calculated using two approximations: the US62 standard atmosphere and the radiosounding launched in Legionowo (12374). The calibration factor CH2O for lidar retrievals was obtained for each profile using the regression method and the profile method to determine the best calibration factor approximation to be used in the final WVMR and RH calculation. Thus, statistically representative results for comparisons between lidar WVMR median profiles obtained by calibrating using radiosounding profiles and using atmospheric synthetic profiles, all of them with the best calibration factor, will be presented. Finally, in order to constrain the conditions of cloud formation in function of the RH profile, the COS14 algorithm, capable of deriving cloud bases and tops by applying thresholds to the RH profiles, was applied to find the cloud vertical structure (CVS). The algorithm was former applied to radiosounding profiles at SGP-ARM site and tested against the CVS obtained from the Active Remote Sensing of Clouds (ARSCL) data. Similarly, it was applied for lidar measurements at the Warsaw measurement site.

Microphysical characterization of winter cloud systems during a research flight campaign

NASA Astrophysics Data System (ADS)

Fernández-González, Sergio; Sánchez, José Luis; Valero, Francisco; Gascón, Estíbaliz; Merino, Andrés; Hermida, Lucía; López, Laura; Marcos, José Luis; García-Ortega, Eduardo

2015-04-01

The lack of accuracy in the knowledge of cloud microphysics leads to aviation risks, which have caused numerous crashes, mainly owing to aircraft icing (e.g., an EMB-120 crashed in Detroit, Michigan in 1997, and an ATR-72 crashed near Roselawn, Indiana in 1994). Further, this lack is a source of uncertainty in numerical weather forecasting models, since commonly used parameterizations often overestimate ice water content and underestimate supercooled liquid water. This makes the collection of data on cloud microphysical characteristics very useful toward improving the forecasting of icing conditions. Ten research flights were conducted during the winters of 2011/12 and 2012/13. Their goal was to determine dominant microphysical conditions of winter cloud systems traversing the Guadarrama Mountains in the central Iberian Peninsula. The aircraft was a C-212-200, equipped with a Cloud, Aerosol, and Precipitation Spectrometer (CAPS) under the left wing. Data of temperature and Liquid Water Content (LWC), registered by the CAPS probe, were used in the study. Furthermore, we thoroughly analyzed images taken by a Cloud Imaging Probe Grayscale (CIP-GS), capable of measuring hydrometeors between 25 and 1,550 µm in size, and representing them in a 2D image. The various types of hydrometeors observed during these flights are described, along with microphysical processes inferred from the CIP-GS images. ACKNOWLEDGEMENTS S. Fernández-González acknowledges grant support from the FPU program (AP 2010-2093). This study was also supported by grants from GRANIMETRO (CGL2010-15930) and MICROMETEO (IPT-310000-2010-22). The authors thank INTA for the research flights.

Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

NASA Astrophysics Data System (ADS)

Collins, Patrick; Bahr, Thomas

2016-04-01

The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of the DEM difference to analyze the surface changes in 3D. The automated point cloud generation and analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the point cloud processing tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study allow a 3D estimation of the topographic changes within the tectonically active and anthropogenically invaded Malin area after the landslide event. Accordingly, the point cloud analysis was correlated successfully with modelled displacement contours of the slope. Based on optical satellite imagery, such point clouds of high precision and density distribution can be obtained in a few minutes to support the operational monitoring of landslide processes.

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

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K.; Miller, David O.

2005-01-01

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

A cloud/particle model of the interstellar medium - Galactic spiral structure

NASA Technical Reports Server (NTRS)

Levinson, F. H.; Roberts, W. W., Jr.

1981-01-01

A cloud/particle model for gas flow in galaxies is developed that incorporates cloud-cloud collisions and supernovae as dominant local processes. Cloud-cloud collisions are the main means of dissipation. To counter this dissipation and maintain local dispersion, supernova explosions in the medium administer radial snowplow pushes to all nearby clouds. The causal link between these processes is that cloud-cloud collisions will form stars and that these stars will rapidly become supernovae. The cloud/particle model is tested and used to investigate the gas dynamics and spiral structures in galaxies where these assumptions may be reasonable. Particular attention is given to whether large-scale galactic shock waves, which are thought to underlie the regular well-delineated spiral structure in some galaxies, form and persist in a cloud-supernova dominated interstellar medium; this question is answered in the affirmative.

Ground-based remote sensing scheme for monitoring aerosol–cloud interactions

DOE PAGES

Sarna, Karolina; Russchenberg, Herman W. J.

2016-03-14

A new method for continuous observation of aerosol–cloud interactions with ground-based remote sensing instruments is presented. The main goal of this method is to enable the monitoring of the change of the cloud droplet size due to the change in the aerosol concentration. We use high-resolution measurements from a lidar, a radar and a radiometer, which allow us to collect and compare data continuously. This method is based on a standardised data format from Cloudnet and can be implemented at any observatory where the Cloudnet data set is available. Two example case studies were chosen from the Atmospheric Radiation Measurementmore » (ARM) Program deployment on Graciosa Island, Azores, Portugal, in 2009 to present the method. We use the cloud droplet effective radius ( r e) to represent cloud microphysical properties and an integrated value of the attenuated backscatter coefficient (ATB) below the cloud to represent the aerosol concentration. All data from each case study are divided into bins of the liquid water path (LWP), each 10 g m -2 wide. For every LWP bin we present the correlation coefficient between ln r e and ln ATB, as well as ACI r (defined as ACI r = -d ln r e d ln ATB, change in cloud droplet effective radius with aerosol concentration). Obtained values of ACI r are in the range 0.01–0.1. In conclusion, we show that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.« less

Challenges in Analyzing and Representing Cloud Microphysical Data Measured with Airborne Cloud Probes

NASA Astrophysics Data System (ADS)

Baumgardner, D.; Freer, M.; McFarquhar, G. M.; Heymsfield, A.; Cziczo, D. J.

2014-12-01

There are a variety of in-situ instruments that are deployed on aircraft for measuring cloud properties, some of which provide data which are used to produce number and mass concentrations of water droplets and ice crystals and their size and shape distributions. Each of these instruments has its strengths and limitations that must be recognized and taken into account during analysis of the data. Various processing techniques have been developed by different groups and techniques implemented to partially correct for the known uncertainties and limitations. The cloud measurement community has in general acknowledged the various issues associated with these instruments and numerous studies have published processing algorithms that seek to improve data quality; however, there has not been a forum in which these various algorithms and processing techniques have been discussed and consensus reached both on optimum analysis strategy and on quantification of uncertainties on the derived data products. Prior to the 2014 AMS Cloud Physics Conference, a study was conducted in which many data sets taken from various aircraft (NCAR-130, North Dakota Citation, Wyoming King Air and FAAM BAE-146) and many instruments (FSSP, CDP, SID, 2D-C/P, CIP/PIP, 2D-S, CPI, Nevzorov Probe and King Hot-wire LWC sensor) were processed by more than 20 individuals or groups to produce a large number of derived products (size distributions, ice fraction, number and mass concentrations, CCN/IN concentrations and median volume diameter). Each person or group that processed a selected data set used their own software and algorithm to produce a secondary data file with derived parameters whose name was encoded to conceal the source of the file so that this was a blind comparison. The workshop that was convened July 5 and 6, 2014, presented the results of the evaluation of the derived products with respect to individual instruments as well as the types of conditions under which the measurements were made. This comparison will ultimately allow quantifying the error bars of derived parameters as a function of the conditions in which the observations are made. The results of this evaluation and the recommendations that evolved from the workshop will be summarized in this presentation.

The fluid dynamics of atmospheric clouds

NASA Astrophysics Data System (ADS)

Randall, David A.

2017-11-01

Clouds of many types are of leading-order importance for Earth's weather and climate. This importance is most often discussed in terms of the effects of clouds on radiative transfer, but the fluid dynamics of clouds are at least equally significant. Some very small-scale cloud fluid-dynamical processes have significant consequences on the global scale. These include viscous dissipation near falling rain drops, and ``buoyancy reversal'' associated with the evaporation of liquid water. Major medium-scale cloud fluid-dynamical processes include cumulus convection and convective aggregation. Planetary-scale processes that depend in an essential way on cloud fluid dynamics include the Madden-Julian Oscillation, which is one of the largest and most consequential weather systems on Earth. I will attempt to give a coherent introductory overview of this broad range of phenomena.

Characterization of the cloud conditions at Ny-Ålesund using sensor synergy and representativeness of the observed clouds across Arctic sites

NASA Astrophysics Data System (ADS)

Nomokonova, Tatiana; Ebell, Kerstin; Löhnert, Ulrich; Maturilli, Marion

2017-04-01

Clouds are one of the crucial components of the hydrological and energy cycles and thus affecting the global climate. Their special importance in Arctic regions is defined by cloud's influence on the radiation budget. Arctic clouds usually occur at low altitudes and often contain highly concentrated tiny liquid drops. During winter, spring, and autumn periods such clouds tend to conserve the long-wave radiation in the atmosphere and, thus, produce warming of the Arctic climate. In summer though clouds efficiently scatter the solar radiation back to space and, therefore, induce a cooling effect. An accurate characterization of the net effect of clouds on the Arctic climate requires long-term and precise observations. However, only a few measurement sites exist which perform continuous, vertically resolved observations of clouds in the Arctic, e.g. in Alaska, Canada, and Greenland. These sites typically make use of a combination of different ground-based remote sensing instruments, e.g. cloud radar, ceilometer and microwave radiometer in order to characterize clouds. Within the Transregional Collaborative Research Center (TR 172) "Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3" comprehensive observations of the atmospheric column are performed at the German-French Research Station AWIPEV at Ny-Ålesund, Svalbard. Ny-Ålesund is located in the warmest part of the Arctic where climate is significantly influenced by adiabatic heating from the warm ocean. Thus, measurements at Ny-Ålesund will complement our understanding of cloud formation and development in the Arctic. This particular study is devoted to the characterization of the cloud macro- and microphysical properties at Ny-Ålesund and of the atmospheric conditions, under which these clouds form and develop. To this end, the information of the various instrumentation at the AWIPEV observatory is synergistically analysed: information about the thermodynamic structure of the atmosphere is obtained from long-term radiosonde launches. In addition, continuous vertical profiles of temperature and humidity are provided by the microwave radiometer HATPRO. A set of active remote sensing instruments performs cloud observations at Ny-Ålesund: a ceilometer and a Doppler lidar operating since 2011 and 2013, respectively, are now complemented with a novel 94 GHz FMCW cloud radar. As a first step, the CLOUDNET algorithms, including a target categorization and classification, are applied to the observations. In this study, we will present a first analysis of cloud properties at Ny-Ålesund including for example cloud occurrence, cloud geometry (cloud base, cloud top, and thickness) and cloud type (liquid, ice, mixed-phase). The different types of clouds are set into context to the environmental conditions such as temperature, amount of water vapour, and liquid water. We also expect that the cloud properties strongly depend on the wind direction. The first results of this analysis will be also shown.

A new airborne sampler for interstitial particles in ice and liquid clouds

NASA Astrophysics Data System (ADS)

Moharreri, A.; Craig, L.; Rogers, D. C.; Brown, M.; Dhaniyala, S.

2011-12-01

In-situ measurements of cloud droplets and aerosols using aircraft platforms are required for understanding aerosol-cloud processes and aiding development of improved aerosol-cloud models. A variety of clouds with different temperature ranges and cloud particle sizes/phases must be studied for comprehensive knowledge about the role of aerosols in the formation and evolution of cloud systems under different atmospheric conditions. While representative aerosol measurements are regularly made from aircrafts under clear air conditions, aerosol measurements in clouds are often contaminated by the generation of secondary particles from the high speed impaction of ice particles and liquid droplets on the surfaces of the aircraft probes/inlets. A new interstitial particle sampler, called the blunt-body aerosol sampler (BASE) has been designed and used for aerosol sampling during two recent airborne campaigns using NCAR/NSF C-130 aircraft: PLOWS (2009-2010) and ICE-T (2011). Central to the design of the new interstitial inlet is an upstream blunt body housing that acts to shield/deflect large cloud droplets and ice particles from an aft sampling region. The blunt-body design also ensures that small shatter particles created from the impaction of cloud-droplets on the blunt-body are not present in the aft region where the interstitial inlet is located. Computational fluid dynamics (CFD) simulations along with particle transport modeling and wind tunnel studies have been utilized in different stages of design and development of this inlet. The initial flights tests during the PLOWS campaign showed that the inlet had satisfactory performance only in warm clouds and when large precipitation droplets were absent. In the presence of large droplets and ice, the inlet samples were contaminated with significant shatter artifacts. These initial results were reanalyzed in conjunction with a computational droplet shatter model and the numerical results were used to arrive at an improved sampler design. Analysis of the data from the recent ICE-T campaign with the improved sampler design shows that the modified version of BASE can provide shatter-artifact free sampling of aerosol particles in the presence of ice particles and significantly reduced shatter artifacts in warm clouds. Detailed design and modeling aspects of the sampler will be discussed and the sampler performance in warm and cold clouds will be presented and compared with measurements made using other aerosol inlets flown on the NCAR/NSF C-130 aircraft.

A Quantitative Investigation of Entrainment and Detrainment in Numerically Simulated Convective Clouds. Pt. 1; Model Development

NASA Technical Reports Server (NTRS)

Cohen, Charles

1998-01-01

A method is developed which uses numerical tracers to make accurate diagnoses of entraimnent and detrainment rates and of the properties of the entrained and detrained air in numerically simulated clouds. The numerical advection scheme is modified to make it nondispersive, as required by the use of the tracers. Tests of the new method are made, and an appropriate definition of clouds is selected. Distributions of mixing fractions in the model consistently show maximums at the end points, for nearly undilute environmental air or nearly undilute cloud air, with a uniform distribution between. The cumulonimbus clouds simulated here entrain air that had been substantially changed by the clouds, and detrained air that is not necessarily representative of the cloud air at the same level.

GEWEX Cloud Systems Study (GCSS)

NASA Technical Reports Server (NTRS)

Moncrieff, Mitch

1993-01-01

The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.

Partitioning CloudSat Ice Water Content for Comparison with Upper-Tropospheric Ice in Global Atmospheric Models

NASA Astrophysics Data System (ADS)

Chen, W. A.; Woods, C. P.; Li, J. F.; Waliser, D. E.; Chern, J.; Tao, W.; Jiang, J. H.; Tompkins, A. M.

2010-12-01

CloudSat provides important estimates of vertically resolved ice water content (IWC) on a global scale based on radar reflectivity. These estimates of IWC have proven beneficial in evaluating the representations of ice clouds in global models. An issue when performing model-data comparisons of IWC particularly germane to this investigation, is the question of which component(s) of the frozen water mass are represented by retrieval estimates and how they relate to what is represented in models. The present study developed and applied a new technique to partition CloudSat total IWC into small and large ice hydrometeors, based on the CloudSat-retrieved ice particle size distribution (PSD) parameters. The new method allows one to make relevant model-data comparisons and provides new insights into the model’s representation of atmospheric IWC. The partitioned CloudSat IWC suggests that the small ice particles contribute to 20-30% of the total IWC in the upper troposphere when a threshold size of 100 μm is used. Sensitivity measures with respect to the threshold size, the PSD parameters, and the retrieval algorithms are presented. The new dataset is compared to model estimates, pointing to areas for model improvement. Cloud ice analyses from the European Centre for Medium-Range Weather Forecasts model agree well with the small IWC from CloudSat. The finite-volume multi-scale modeling framework model underestimates total IWC at 147 and 215 hPa, while overestimating the fractional contribution from the small ice species. These results are discussed in terms of their applications to, and implications for, the evaluation of global atmospheric models, providing constraints on the representations of cloud feedback and precipitation in global models, which in turn can help reduce uncertainties associated with climate change projections. Figure 1. A sample lognormal ice number distribution (red curve), and the corresponding mass distribution (black curve). The dotted line represents the cutoff size for IWC partitioning (Dc = 100 µm as an example). The partial integrals of the mass distribution for particles smaller and larger than Dc correspond to IWC<100 (green area) and IWC>100 (blue area), respectively.

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

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

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

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

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

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

Optical observations of electrical activity in cloud discharges

NASA Astrophysics Data System (ADS)

Vayanganie, S. P. A.; Fernando, M.; Sonnadara, U.; Cooray, V.; Perera, C.

2018-07-01

Temporal variation of the luminosity of seven natural cloud-to-cloud lightning channels were studied, and results were presented. They were recorded by using a high-speed video camera with the speed of 5000 fps (frames per second) and the pixel resolution of 512 × 512 in three locations in Sri Lanka in the tropics. Luminosity variation of the channel with time was obtained by analyzing the image sequences. Recorded video frames together with the luminosity variation were studied to understand the cloud discharge process. Image analysis techniques also used to understand the characteristics of channels. Cloud flashes show more luminosity variability than ground flashes. Most of the time it starts with a leader which do not have stepping process. Channel width and standard deviation of intensity variation across the channel for each cloud flashes was obtained. Brightness variation across the channel shows a Gaussian distribution. The average time duration of the cloud flashes which start with non stepped leader was 180.83 ms. Identified characteristics are matched with the existing models to understand the process of cloud flashes. The fact that cloud discharges are not confined to a single process have been further confirmed from this study. The observations show that cloud flash is a basic lightning discharge which transfers charge between two charge centers without using one specific mechanism.

Aerosol physicochemical properties in relation to meteorology: Case studies in urban, marine, and arid settings

NASA Astrophysics Data System (ADS)

Wonaschuetz, Anna

Atmospheric aerosols are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrological cycle. As opposed to other key atmospheric constituents with climatic relevance, atmospheric aerosol particles are highly heterogeneous in time and space with respect to their size, concentration, chemical composition and physical properties. Many aspects of their life cycle are not understood, making them difficult to represent in climate models and hard to control as a pollutant. Aerosol-cloud interactions in particular are infamous as a major source of uncertainty in future climate predictions. Field measurements are an important source of information for the modeling community and can lead to a better understanding of chemical and microphysical processes. In this study, field data from urban, marine, and arid settings are analyzed and the impact of meteorological conditions on the evolution of aerosol particles while in the atmosphere is investigated. Particular attention is given to organic aerosols, which are a poorly understood component of atmospheric aerosols. Local wind characteristics, solar radiation, relative humidity and the presence or absence of clouds and fog are found to be crucial factors in the transport and chemical evolution of aerosol particles. Organic aerosols in particular are found to be heavily impacted by processes in the liquid phase (cloud droplets and aerosol water). The reported measurements serve to improve the process-level understanding of aerosol evolution in different environments and to inform the modeling community by providing realistic values for input parameters and validation of model calculations.

Impacts of Subgrid Heterogeneous Mixing between Cloud Liquid and Ice on the Wegner-Bergeron-Findeisen Process and Mixed-phase Clouds in NCAR CAM5

NASA Astrophysics Data System (ADS)

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

2017-12-01

Mixed-phase clouds are persistently observed over the Arctic and the phase partitioning between cloud liquid and ice hydrometeors in mixed-phase clouds has important impacts on the surface energy budget and Arctic climate. In this study, we test the NCAR Community Atmosphere Model Version 5 (CAM5) with the single-column and weather forecast configurations and evaluate the model performance against observation data from the DOE Atmospheric Radiation Measurement (ARM) Program's M-PACE field campaign in October 2004 and long-term ground-based multi-sensor remote sensing measurements. Like most global climate models, we find that CAM5 also poorly simulates the phase partitioning in mixed-phase clouds by significantly underestimating the cloud liquid water content. Assuming pocket structures in the distribution of cloud liquid and ice in mixed-phase clouds as suggested by in situ observations provides a plausible solution to improve the model performance by reducing the Wegner-Bergeron-Findeisen (WBF) process rate. In this study, the modification of the WBF process in the CAM5 model has been achieved with applying a stochastic perturbation to the time scale of the WBF process relevant to both ice and snow to account for the heterogeneous mixture of cloud liquid and ice. Our results show that this modification of WBF process improves the modeled phase partitioning in the mixed-phase clouds. The seasonal variation of mixed-phase cloud properties is also better reproduced in the model in comparison with the long-term ground-based remote sensing observations. Furthermore, the phase partitioning is insensitive to the reassignment time step of perturbations.

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

DOE PAGES

Prather, M. J.

2015-05-27

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

PAHs molecules and heating of the interstellar gas

NASA Technical Reports Server (NTRS)

Verstraete, Laurent; Leger, Alain; Dhendecourt, Louis B.; Dutuit, O.; Defourneau, D.

1989-01-01

Until now it has remained difficult to account for the rather high temperatures seen in many diffuse interstellar clouds. Various heating mechanisms have been considered: photoionization of minor species, ionization of H by cosmic rays, and photoelectric effect on small grains. Yet all these processes are either too weak or efficient under too restricting conditions to balance the observed cooling rates. A major heat source is thus still missing in the thermal balance of the diffuse gas. Using photoionization cross sections measured in the lab, it was shown that in order to balance the observed cooling rates in cold diffuse clouds (T approx. 80 K) the PAHs would have to contain 15 percent of the cosmic abundance of carbon. This value does not contradict the former estimation of 6 percent deduced from the IR emission bands since this latter is to be taken as a lower limit. Further, it was estimated that the contribution to the heating rate due to PAH's in a warm HI cloud, assuming the same PAH abundance as for a cold HI cloud, would represent a significant fraction of the value required to keep the medium in thermal balance. Thus, photoionization of PAHs might well be a major heat source for the cold and warm HI media.

Network approach to patterns in stratocumulus clouds

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds.

PubMed

Glassmeier, Franziska; Feingold, Graham

2017-10-03

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Impact of capturing rainfall scavenging intermittency using cloud superparameterization on simulated continental scale wildfire smoke transport

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Kooperman, G. J.; Zhao, Z.; Wang, M.; Russell, L. M.; Somerville, R. C.; Ghan, S. J.

2011-12-01

Evaluating the fidelity of new aerosol physics in climate models is confounded by uncertainties in source emissions, systematic error in cloud parameterizations, and inadequate sampling of long-range plume concentrations. To explore the degree to which cloud parameterizations distort aerosol processing and scavenging, the Pacific Northwest National Laboratory (PNNL) Aerosol-Enabled Multi-Scale Modeling Framework (AE-MMF), a superparameterized branch of the Community Atmosphere Model Version 5 (CAM5), is applied to represent the unusually active and well sampled North American wildfire season in 2004. In the AE-MMF approach, the evolution of double moment aerosols in the exterior global resolved scale is linked explicitly to convective statistics harvested from an interior cloud resolving scale. The model is configured in retroactive nudged mode to observationally constrain synoptic meteorology, and Arctic wildfire activity is prescribed at high space/time resolution using data from the Global Fire Emissions Database. Comparisons against standard CAM5 bracket the effect of superparameterization to isolate the role of capturing rainfall intermittency on the bulk characteristics of 2004 Arctic plume transport. Ground based lidar and in situ aircraft wildfire plume constraints from the International Consortium for Atmospheric Research on Transport and Transformation field campaign are used as a baseline for model evaluation.

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.

Network approach to patterns in stratocumulus clouds

PubMed Central

Feingold, Graham

2017-01-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes. PMID:28904097

- 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.

Observing Ice in Clouds from Space

NASA Technical Reports Server (NTRS)

Ackerman, S.; Star, D. O'C.; Skofronick-Jackson, G.; Evans, F.; Wang, J. R.; Norris, P.; daSilva, A.; Soden, B.

2006-01-01

There are many satellite observations of cloud top properties and the liquid and rain content of clouds, however, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds in the upper troposphere either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. These properties include cloud horizontal and vertical structure, cloud water content and some measure of particle sizes and shapes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. One barrier to achieving accurate global ice cloud properties is the lack of adequate observations at millimeter and submillimeter wavelengths (183-874 GHz). Recent advances in instrumentation have allowed for the development and implementation of an airborne submillimeter-wave radiometer. The brightness temperatures at these frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. The next step is a satellite mission designed to acquire global Earth radiance measurements in the submillimeter-wave region, thus bridging the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. This presentation provides scientific justification and an approach to measuring ice water path and particle size from a satellite platform that spans a range encompassing both the hydrologically active and radiatively active components of cloud systems.

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]. Please see Tao et al. (2007) for more detailed description on aerosol impact on precipitation. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. 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 summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

Planetary astronomy

NASA Technical Reports Server (NTRS)

1976-01-01

Color and spectral data from spectrometer observations and computerized analyses of asteroid spectra are discussed. Potential occultations of bright asteroids by the moon are summarized. Analysis of anisotropic scattering within Saturn's rings indicates that mineral contamination of the 120 particles cannot exceed 5 percent by weight, and that the rings formed from particle breakup rather than from particle condensation. Raman probe applications to Jupiter and Uranus atmospheres indicate the presence of aerosol particles. A review of Mariner 9 Mars cloud topography data establishes that most blue clouds are orographic uplift clouds composed of condensates, and that sporadic red clouds are associated with blue clouds or volcanoes and thus probably do not represent dust storm phenomena.

Automatic cloud coverage assessment of Formosat-2 image

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2011-11-01

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

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

DOE PAGES

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

2015-06-30

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

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

DOE PAGES

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

2015-12-01

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

Sentinel-1 Archive and Processing in the Cloud using the Hybrid Pluggable Processing Pipeline (HyP3) at the ASF DAAC

NASA Astrophysics Data System (ADS)

Arko, S. A.; Hogenson, R.; Geiger, A.; Herrmann, J.; Buechler, B.; Hogenson, K.

2016-12-01

In the coming years there will be an unprecedented amount of SAR data available on a free and open basis to research and operational users around the globe. The Alaska Satellite Facility (ASF) DAAC hosts, through an international agreement, data from the Sentinel-1 spacecraft and will be hosting data from the upcoming NASA ISRO SAR (NISAR) mission. To more effectively manage and exploit these vast datasets, ASF DAAC has begun moving portions of the archive to the cloud and utilizing cloud services to provide higher-level processing on the data. The Hybrid Pluggable Processing Pipeline (HyP3) project is designed to support higher-level data processing in the cloud and extend the capabilities of researchers to larger scales. Built upon a set of core Amazon cloud services, the HyP3 system allows users to request data processing using a number of canned algorithms or their own algorithms once they have been uploaded to the cloud. The HyP3 system automatically accesses the ASF cloud-based archive through the DAAC RESTful application programming interface and processes the data on Amazon's elastic compute cluster (EC2). Final products are distributed through Amazon's simple storage service (S3) and are available for user download. This presentation will provide an overview of ASF DAAC's activities moving the Sentinel-1 archive into the cloud and developing the integrated HyP3 system, covering both the benefits and difficulties of working in the cloud. Additionally, we will focus on the utilization of HyP3 for higher-level processing of SAR data. Two example algorithms, for sea-ice tracking and change detection, will be discussed as well as the mechanism for integrating new algorithms into the pipeline for community use.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

CloudSat First Image of a Warm Front Storm Over the Norwegian Sea

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat's first image, of a warm front storm over the Norwegian Sea, was obtained on May 20, 2006. In this horizontal cross-section of clouds, warm air is seen rising over colder air as the satellite travels from right to left. The red colors are indicative of highly reflective particles such as water droplets (or rain) or larger ice crystals (or snow), while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.

CloudSat Image of a Polar Night Storm Near Antarctica

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat image of a horizontal cross-section of a polar night storm near Antarctica. Until now, clouds have been hard to observe in polar regions using remote sensing, particularly during the polar winter or night season. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water; the brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.

A Stochastic Approach For Extending The Dimensionality Of Observed Datasets

NASA Technical Reports Server (NTRS)

Varnai, Tamas

2002-01-01

This paper addresses the problem that in many cases, observations cannot provide complete fields of the measured quantities, because they yield data only along a single cross-section through the examined fields. The paper describes a new Fourier-adjustment technique that allows existing fractal models to build realistic surroundings to the measured cross-sections. This new approach allows more representative calculations of cloud radiative processes and may be used in other areas as well.

Toward a more physical representation of precipitation scavenging in global chemistry models: cloud overlap and ice physics and their impact on tropospheric ozone

NASA Astrophysics Data System (ADS)

Neu, J. L.; Prather, M. J.

2011-08-01

Uptake and removal of soluble trace gases and aerosols by precipitation represents a major uncertainty in the processes that control the vertical distribution of atmospheric trace species. Model representations of precipitation scavenging vary greatly in their complexity, and most are divorced from the physics of precipitation formation and transformation. Here, we describe a new large-scale precipitation scavenging algorithm, developed for the UCI chemistry-transport model (UCI-CTM), that represents a step toward a more physical treatment of scavenging through improvements in the formulation of the removal in sub-gridscale cloudy and ambient environments and their overlap within the column as well as ice phase uptake of soluble species. The UCI algorithm doubles the lifetime of HNO3 in the upper troposphere relative to a scheme with commonly made assumptions about cloud overlap and ice uptake, and provides better agreement with HNO3 observations. We find that the process of ice phase scavenging of HNO3 is a critical component of the tropospheric O3 budget, but that differences in the formulation of ice phase removal, while generating large relative differences in HNO3 abundance, have little impact on NOx and O3. The O3 budget is much more sensitive to the lifetime of HNO4, highlighting the need for better understanding of its interactions with ice and for additional observational constraints.

Toward a more physical representation of precipitation scavenging in global chemistry models: cloud overlap and ice physics and their impact on tropospheric ozone

NASA Astrophysics Data System (ADS)

Neu, J. L.; Prather, M. J.

2012-04-01

Uptake and removal of soluble trace gases and aerosols by precipitation represents a major uncertainty in the processes that control the vertical distribution of atmospheric trace species. Model representations of precipitation scavenging vary greatly in their complexity, and most are divorced from the physics of precipitation formation and transformation. Here, we describe a new large-scale precipitation scavenging algorithm, developed for the UCI chemistry-transport model (UCI-CTM), that represents a step toward a more physical treatment of scavenging through improvements in the formulation of the removal in sub-gridscale cloudy and ambient environments and their overlap within the column as well as ice phase uptake of soluble species. The UCI algorithm doubles the lifetime of HNO3 in the upper troposphere relative to a scheme with commonly used fractional cloud cover assumptions and ice uptake determined by Henry's Law and provides better agreement with HNO3 observations. We find that the process of ice phase scavenging of HNO3 is a critical component of the tropospheric O3 budget, but that NOx and O3 mixing ratios are relatively insensitive to large differences in the removal rate. Ozone abundances are much more sensitive to the lifetime of HNO4, highlighting the need for better understanding of its interactions with ice and for additional observational constraints.

ARC-1989-AC89-0114-592

NASA Image and Video Library

1989-02-28

Airborne Arctic Stratospheric (Ozone) Expedition Stavanger Norway Jan-Feb 1989: The clouds seen from the NASA DC-8 aircraft at nearly 39,000 feet in the polar regions north of Stravanger, Norway, are representative of what are called 'Type II' polar stratospheric clouds. This type consists mostly of water molecules frozen as ice. These particular clouds are also exhibiting what is called orographic effects - the clouds have taken on a wave-like form because of motion associated with underlying topographic features of the earth's surface; in this case, some mountains in Iceland.

Towards a Cloud Computing Environment: Near Real-time Cloud Product Processing and Distribution for Next Generation Satellites

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Palikonda, R.; Smith, W. L., Jr.; Spangenberg, D.

2016-12-01

The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) processes and derives near real-time (NRT) global cloud products from operational geostationary satellite imager datasets. These products are being used in NRT to improve forecast model, aircraft icing warnings, and support aircraft field campaigns. Next generation satellites, such as the Japanese Himawari-8 and the upcoming NOAA GOES-R, present challenges for NRT data processing and product dissemination due to the increase in temporal and spatial resolution. The volume of data is expected to increase to approximately 10 folds. This increase in data volume will require additional IT resources to keep up with the processing demands to satisfy NRT requirements. In addition, these resources are not readily available due to cost and other technical limitations. To anticipate and meet these computing resource requirements, we have employed a hybrid cloud computing environment to augment the generation of SatCORPS products. This paper will describe the workflow to ingest, process, and distribute SatCORPS products and the technologies used. Lessons learn from working on both AWS Clouds and GovCloud will be discussed: benefits, similarities, and differences that could impact decision to use cloud computing and storage. A detail cost analysis will be presented. In addition, future cloud utilization, parallelization, and architecture layout will be discussed for GOES-R.

An Imager Gaussian Process Machine Learning Methodology for Cloud Thermodynamic Phase classification

NASA Astrophysics Data System (ADS)

Marchant, B.; Platnick, S. E.; Meyer, K.

2017-12-01

The determination of cloud thermodynamic phase from MODIS and VIIRS instruments is an important first step in cloud optical retrievals, since ice and liquid clouds have different optical properties. To continue improving the cloud thermodynamic phase classification algorithm, a machine-learning approach, based on Gaussian processes, has been developed. The new proposed methodology provides cloud phase uncertainty quantification and improves the algorithm portability between MODIS and VIIRS. We will present new results, through comparisons between MODIS and CALIOP v4, and for VIIRS as well.

Cloud Based Applications and Platforms (Presentation)

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

Brodt-Giles, D.

2014-05-15

Presentation to the Cloud Computing East 2014 Conference, where we are highlighting our cloud computing strategy, describing the platforms on the cloud (including Smartgrid.gov), and defining our process for implementing cloud based applications.

On the Cloud Observations in JAXA's Next Coming Satellite Missions

NASA Technical Reports Server (NTRS)

Nakajima, Takashi Y.; Nagao, Takashi M.; Letu, Husi; Ishida, Haruma; Suzuki, Kentaroh

2012-01-01

The use of JAXA's next generation satellites, the EarthCARE and the GCOM-C, for observing overall cloud systems on the Earth is discussed. The satellites will be launched in the middle of 2010-era and contribute for observing aerosols and clouds in terms of climate change, environment, weather forecasting, and cloud revolution process study. This paper describes the role of such satellites and how to use the observing data showing concepts and some sample viewgraphs. Synergistic use of sensors is a key of the study. Visible to infrared bands are used for cloudy and clear discriminating from passively obtained satellite images. Cloud properties such as the cloud optical thickness, the effective particle radii, and the cloud top temperature will be retrieved from visible to infrared wavelengths of imagers. Additionally, we are going to combine cloud properties obtained from passive imagers and radar reflectivities obtained from an active radar in order to improve our understanding of cloud evolution process. This is one of the new techniques of satellite data analysis in terms of cloud sciences in the next decade. Since the climate change and cloud process study have mutual beneficial relationship, a multispectral wide-swath imagers like the GCOM-C SGLI and a comprehensive observation package of cloud and aerosol like the EarthCARE are both necessary.

Atmospheric State, Cloud Microphysics and Radiative Flux

DOE Data Explorer

Mace, Gerald

2008-01-15

Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the physical state of the atmospheric column compiled on a five-minute temporal and 90m vertical grid. Sources for this information include raw measurements, cloud property and radiative retrievals, retrievals and derived variables from other third-party sources, and radiative calculations using the derived quantities.

Biomedical image analysis and processing in clouds

NASA Astrophysics Data System (ADS)

Bednarz, Tomasz; Szul, Piotr; Arzhaeva, Yulia; Wang, Dadong; Burdett, Neil; Khassapov, Alex; Chen, Shiping; Vallotton, Pascal; Lagerstrom, Ryan; Gureyev, Tim; Taylor, John

2013-10-01

Cloud-based Image Analysis and Processing Toolbox project runs on the Australian National eResearch Collaboration Tools and Resources (NeCTAR) cloud infrastructure and allows access to biomedical image processing and analysis services to researchers via remotely accessible user interfaces. By providing user-friendly access to cloud computing resources and new workflow-based interfaces, our solution enables researchers to carry out various challenging image analysis and reconstruction tasks. Several case studies will be presented during the conference.

Big Geo Data Services: From More Bytes to More Barrels

NASA Astrophysics Data System (ADS)

Misev, Dimitar; Baumann, Peter

2016-04-01

The data deluge is affecting the oil and gas industry just as much as many other industries. However, aside from the sheer volume there is the challenge of data variety, such as regular and irregular grids, multi-dimensional space/time grids, point clouds, and TINs and other meshes. A uniform conceptualization for modelling and serving them could save substantial effort, such as the proverbial "department of reformatting". The notion of a coverage actually can accomplish this. Its abstract model in ISO 19123 together with the concrete, interoperable OGC Coverage Implementation Schema (CIS), which is currently under adoption as ISO 19123-2, provieds a common platform for representing any n-D grid type, point clouds, and general meshes. This is paired by the OGC Web Coverage Service (WCS) together with its datacube analytics language, the OGC Web Coverage Processing Service (WCPS). The OGC WCS Core Reference Implementation, rasdaman, relies on Array Database technology, i.e. a NewSQL/NoSQL approach. It supports the grid part of coverages, with installations of 100+ TB known and single queries parallelized across 1,000+ cloud nodes. Recent research attempts to address the point cloud and mesh part through a unified query model. The Holy Grail envisioned is that these approaches can be merged into a single service interface at some time. We present both grid amd point cloud / mesh approaches and discuss status, implementation, standardization, and research perspectives, including a live demo.

Automatic Generation of Indoor Navigable Space Using a Point Cloud and its Scanner Trajectory

NASA Astrophysics Data System (ADS)

Staats, B. R.; Diakité, A. A.; Voûte, R. L.; Zlatanova, S.

2017-09-01

Automatic generation of indoor navigable models is mostly based on 2D floor plans. However, in many cases the floor plans are out of date. Buildings are not always built according to their blue prints, interiors might change after a few years because of modified walls and doors, and furniture may be repositioned to the user's preferences. Therefore, new approaches for the quick recording of indoor environments should be investigated. This paper concentrates on laser scanning with a Mobile Laser Scanner (MLS) device. The MLS device stores a point cloud and its trajectory. If the MLS device is operated by a human, the trajectory contains information which can be used to distinguish different surfaces. In this paper a method is presented for the identification of walkable surfaces based on the analysis of the point cloud and the trajectory of the MLS scanner. This method consists of several steps. First, the point cloud is voxelized. Second, the trajectory is analysing and projecting to acquire seed voxels. Third, these seed voxels are generated into floor regions by the use of a region growing process. By identifying dynamic objects, doors and furniture, these floor regions can be modified so that each region represents a specific navigable space inside a building as a free navigable voxel space. By combining the point cloud and its corresponding trajectory, the walkable space can be identified for any type of building even if the interior is scanned during business hours.

The 90 GHz radiometric imaging. [for terrain analysis

NASA Technical Reports Server (NTRS)

King, H. E.; White, J. D.; Wilson, W. J.; Mori, T. T.; Hollinger, J. P.; Troy, B. E.; Kenney, J. E.; Mcgoogan, J. T.

1976-01-01

A 90-GHz (3 mm wavelength) radiometer with a noise output fluctuation of 0.22 K (RMS), with a scanning antenna beam mirror, and the data processing system are described. Real-time radiometric imaging of terrain and man-made objects are shown. Flying at an altitude of 1500 ft a radiometer antenna with a 2 degrees halfpower beamwidth can distinguish landforms, waterways, roads, runways, bridges, ships at sea and their wakes, aircraft on runways, and athletic fields. A flight taken at an altitude of 3000 ft with approximately 2000 ft of clouds below the radiometer demonstrates the ability to distinguish bridges, rivers, marshland and other landforms even though the clouds are optically opaque. The radiometric images of a few representative scenes along with photographs of the corresponding scenes are presented to demonstrate the resolution of the imager system.

Atmospheric System Research Marine Low Clouds Workshop Report, January 27-29,2016

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

Jensen, M.; Wang, J.; Wood, R.

Marine low clouds are a major determinant of the Earth?s albedo and are a major source of uncertainty in how the climate responds to changing greenhouse gas levels and anthropogenic aerosol. Marine low clouds are particularly difficult to simulate accurately in climate models, and their remote locations present a significant observational challenge. A complex set of interacting controlling processes determine the coverage, condensate loading, and microphysical and radiative properties of marine low clouds. Marine low clouds are sensitive to atmospheric aerosol in several ways. Interactions at microphysical scales involve changes in the concentration of cloud droplets and precipitation, which inducemore » cloud dynamical impacts including changes in entrainment and mesoscale organization. Marine low clouds are also impacted by atmospheric heating changes due to absorbing aerosols. The response of marine low clouds to aerosol perturbations depends strongly upon the unperturbed aerosol-cloud state, which necessitates greater understanding of processes controlling the budget of aerosol in the marine boundary layer. Entrainment and precipitation mediate the response of low clouds to aerosols but these processes also play leading roles in controlling the aerosol budget. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility and Atmospheric System Research (ASR) program are making major recent investments in observational data sets from fixed and mobile sites dominated by marine low clouds. This report provides specific action items for how these measurements can be used together with process modeling to make progress on understanding and quantifying the key cloud and aerosol controlling processes in the next 5-10 years. Measurements of aerosol composition and its variation with particle size are needed to advance a quantitative, process-level understanding of marine boundary-layer aerosol budget. Quantitative precipitation estimates that combine radar and lidar measurements are becoming available, and these could be used to test process models, quantify precipitation responses to aerosol, and constrain climate models. Models and observations can be used to constrain how clouds respond dynamically to changing precipitation. New measurements of turbulence from ground-based remote sensing could be used to attempt to relate entrainment to the vertical and horizontal structure of turbulence in the boundary layer. Cloud-top entrainment plays a major role in modulating how low clouds respond to both aerosols and to greenhouse gases, so investment in promising new observational estimates would be beneficial. Precipitation formation and radiative cooling both help marine low clouds to organize on the mesoscale. More work is needed to develop metrics to characterize mesoscale organization, to elucidate mechanisms that determine the type and spatial scale of mesoscale cellular convection, and to understand the role of mesoscale structures in the stratocumulus-to-cumulus transition.« less

iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

PubMed

Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

2016-11-01

To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

The Arctic clouds from model simulations and long-term observations at Barrow, Alaska

NASA Astrophysics Data System (ADS)

Zhao, Ming

The Arctic is a region that is very sensitive to global climate change while also experiencing significant changes in its surface air temperature, sea-ice cover, atmospheric circulation, precipitation, snowfall, biogeochemical cycling, and land surface. Although previous studies have shown that the arctic clouds play an important role in the arctic climate changes, the arctic clouds are poorly understood and simulated in climate model due to limited observations. Furthermore, most of the studies were based on short-term experiments and typically only cover the warm seasons, which do not provide a full understanding of the seasonal cycle of arctic clouds. To address the above concerns and to improve our understanding of arctic clouds, six years of observational and retrieval data from 1999 to 2004 at the Atmospheric Radiation Management (ARM) Climate Research Facility (ACRF) North Slope of Alaska (NSA) Barrow site are used to understand the arctic clouds and related radiative processes. In particular, we focus on the liquid-ice mass partition in the mixed-phase cloud layer. Statistical results show that aerosol type and concentration are important factors that impact the mixed-phase stratus (MPS) cloud microphysical properties: liquid water path (LWP) and liquid water fraction (LWF) decrease with the increase of cloud condensation nuclei (CCN) number concentration; the high dust loading and dust occurrence in the spring are possible reasons for the much lower LWF than the other seasons. The importance of liquid-ice mass partition on surface radiation budgets was analyzed by comparing cloud longwave radiative forcings under the same LWP but different ice water path (IWP) ranges. Results show the ice phase enhance the surface cloud longwave (LW) forcing by 8˜9 W m-2 in the moderately thin MPS. This result provides an observational evidence on the aerosol glaciation effect in the moderately thin MPS, which is largely unknown so far. The above new insights are important to guide the model parameterizations of liquid-ice mass partition in arctic mixed-phase clouds, and are served as a test bed to cloud models and cloud microphysical schemes. The observational data between 1999 and 2007 are used to assess the performance of the European Center for Medium-Range Weather Forecasts (ECMWF) model in the Arctic region. The ECMWF model-simulated near-surface humidity had seasonal dependent biases as large as 20%, while also experiencing difficulty representing boundary layer (BL) temperature inversion height and strength during the transition seasons. Although the ECMWF model captured the seasonal variation of surface heat fluxes, it had sensible heat flux biases over 20 W m-2 in most of the cold months. Furthermore, even though the model captured the general seasonal variations of low-level cloud fraction (LCF) and LWP, it still overestimated the LCF by 20% or more and underestimated the LWP over 50% in the cold season. On average, the ECMWF model underestimated LWP by ˜30 g m-2 but more accurately predicted ice water path for BL clouds. For BL mixed-phase clouds, the model predicted water-ice mass partition was significantly lower than the observations, largely due to the temperature dependence of water-ice mass partition used in the model. The new cloud and BL schemes of the ECMWF model that were implemented after 2003 only resulted in minor improvements in BL cloud simulations in summer. These results indicate that significant improvements in cold season BL and mixed-phase cloud processes in the model are needed. In this study, single-layer MPS clouds were simulated by the Weather Research and Forecasting (WRF) model under different microphysical schemes and different ice nuclei (IN) number concentrations. Results show that by using proper IN concentration, the WRF model incorporated with Morrison microphysical scheme can reasonably capture the observed seasonal differences in temperature dependent liquid-ice mass partition. However, WRF simulations underestimate both LWP and IWP indicating its deficiency in capturing the radiative impacts of arctic MPS clouds.

Process-model Simulations of Cloud Albedo Enhancement by Aerosols in the Arctic

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

Kravitz, Benjamin S.; Wang, Hailong; Rasch, Philip J.

2014-11-17

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN). An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Because nearly all of the albedo effects are in the liquid phase due to the removal of ice water by snowfall when ice processes are involved, albedo increases are stronger for pure liquid clouds than mixed-phase clouds.more » Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation due to precipitation changes are small.« less

Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Potter, G. L.; Blanchet, J. P.; Boer, G. J.; Del Genio, A. D.

1990-01-01

The present study provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphazied that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback.

A Mission to Observe Ice in Clouds from Space

NASA Technical Reports Server (NTRS)

Ackerman, S.; O'CStarr, D.; Skofronick-Jackson, G.; Evans, F.; Wang, J. R.; Racette, P.; Norris, P.; daSilva, A.; Soden, B.

2006-01-01

To date there have been multiple satellite missions to observe and retrieve cloud top properties and the liquid in, and precipitation from, clouds. There are currently a few missions that attempt to measure cloud ice properties as a byproduct of other observations. However, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. This presentation will describe the Submillimeter-wave InfraRed Ice Cloud Experiment (SIRICE) concept, a satellite mission designed to acquire global Earth radiance measurements in the infrared and submillimeter-wave region (183-874 GHz). If successful, this mission will bridge the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. The brightness temperatures at submillimeter-wave frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. Scientific justification and the SIRICE approach to measuring ice water path and particle size that span a range encompassing both the hydrologically active and radiatively active components of cloud systems will be presented.

Cloud processing of organic compounds: Secondary organic aerosol and nitrosamine formation

NASA Astrophysics Data System (ADS)

Hutchings, James W., III

Cloud processing of atmospheric organic compounds has been investigated through field studies, laboratory experiments, and numerical modeling. Observational cloud chemistry studies were performed in northern Arizona and fog studies in central Pennsylvania. At both locations, the cloud and fogs showed low acidity due to neutralization by soil dust components (Arizona) and ammonia (Pennsylvania). The field observations showed substantial concentrations (20-5500 ng•L -1) of volatile organic compounds (VOC) in the cloud droplets. The potential generation of secondary organic aerosol mass through the processing of these anthropogenic VOCs was investigated through laboratory and modeling studies. Under simulated atmospheric conditions, in idealized solutions, benzene, toluene, ethylbenzene, and xylene (BTEX) degraded quickly in the aqueous phase with half lives of approximately three hours. The degradation process yielded less volatile products which would contribute to new aerosol mass upon cloud evaporation. However, when realistic cloud solutions containing natural organic matter were used in the experiments, the reaction kinetics decreased with increasing organic carbon content, resulting in half lives of approximately 7 hours. The secondary organic aerosol (SUA) mass formation potential of cloud processing of BTEX was evaluated. SOA mass formation by cloud processing of BTEX, while strongly dependent on the atmospheric conditions, could contribute up to 9% of the ambient atmospheric aerosol mass, although typically ˜1% appears realistic. Field observations also showed the occurrence of N-nitrosodimethylamine (NDMA), a potent carcinogen, in fogs and clouds (100-340 ng•L -1). Laboratory studies were conducted to investigate the formation of NDMA from nitrous acid and dimethylamine in the homogeneous aqueous phase within cloud droplets. While NDMA was produced in the cloud droplets, the low yields (<1%) observed could not explain observational concentrations. Therefore heterogeneous or gaseous formation of NDMA with partitioning to droplet must be the source of aqueous NDMA. Box-model calculations tended to demonstrate a predominance of a gas phase formation mechanism followed by partitioning into the cloud droplets. The calculations were consistent with field measurements of gaseous and aqueous NDMA concentrations. Measurements and model calculations showed that while NDMA is eventually photolyzed, it might persist in the atmosphere for hours.

Confronting Models with Data: The GEWEX Cloud Systems Study

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing

NASA Astrophysics Data System (ADS)

Klems, Markus; Nimis, Jens; Tai, Stefan

On-demand provisioning of scalable and reliable compute services, along with a cost model that charges consumers based on actual service usage, has been an objective in distributed computing research and industry for a while. Cloud Computing promises to deliver on this objective: consumers are able to rent infrastructure in the Cloud as needed, deploy applications and store data, and access them via Web protocols on a pay-per-use basis. The acceptance of Cloud Computing, however, depends on the ability for Cloud Computing providers and consumers to implement a model for business value co-creation. Therefore, a systematic approach to measure costs and benefits of Cloud Computing is needed. In this paper, we discuss the need for valuation of Cloud Computing, identify key components, and structure these components in a framework. The framework assists decision makers in estimating Cloud Computing costs and to compare these costs to conventional IT solutions. We demonstrate by means of representative use cases how our framework can be applied to real world scenarios.

Strong Constraints on Aerosol-Cloud Interactions from Volcanic Eruptions

NASA Technical Reports Server (NTRS)

Malavelle, Florent F.; Haywood, Jim M.; Jones, Andy; Gettelman, Andrew; Clarisse, Lieven; Bauduin, Sophie; Allan, Richard P.; Karset, Inger Helene H.; Kristjansson, Jon Egill; Oreopoulos, Lazaros;

Strong constraints on aerosol-cloud interactions from volcanic eruptions.

PubMed

Malavelle, Florent F; Haywood, Jim M; Jones, Andy; Gettelman, Andrew; Clarisse, Lieven; Bauduin, Sophie; Allan, Richard P; Karset, Inger Helene H; Kristjánsson, Jón Egill; Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Bellouin, Nicolas; Boucher, Olivier; Grosvenor, Daniel P; Carslaw, Ken S; Dhomse, Sandip; Mann, Graham W; Schmidt, Anja; Coe, Hugh; Hartley, Margaret E; Dalvi, Mohit; Hill, Adrian A; Johnson, Ben T; Johnson, Colin E; Knight, Jeff R; O'Connor, Fiona M; Partridge, Daniel G; Stier, Philip; Myhre, Gunnar; Platnick, Steven; Stephens, Graeme L; Takahashi, Hanii; Thordarson, Thorvaldur

2017-06-22

Aerosols have a potentially large effect on climate, particularly through their interactions with clouds, but the magnitude of this effect is highly uncertain. Large volcanic eruptions produce sulfur dioxide, which in turn produces aerosols; these eruptions thus represent a natural experiment through which to quantify aerosol-cloud interactions. Here we show that the massive 2014-2015 fissure eruption in Holuhraun, Iceland, reduced the size of liquid cloud droplets-consistent with expectations-but had no discernible effect on other cloud properties. The reduction in droplet size led to cloud brightening and global-mean radiative forcing of around -0.2 watts per square metre for September to October 2014. Changes in cloud amount or cloud liquid water path, however, were undetectable, indicating that these indirect effects, and cloud systems in general, are well buffered against aerosol changes. This result will reduce uncertainties in future climate projections, because we are now able to reject results from climate models with an excessive liquid-water-path response.

Aqueous Processing of Atmospheric Organic Particles in Cloud Water Collected via Aircraft Sampling

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

Boone, Eric J.; Laskin, Alexander; Laskin, Julia

2015-07-21

Cloud water and below-cloud atmospheric particle samples were collected onboard a research aircraft during the Southern Oxidant and Aerosol Study (SOAS) over a forested region of Alabama in June 2013. The organic molecular composition of the samples was studied to gain insights into the aqueous-phase processing of organic compounds within cloud droplets. High resolution mass spectrometry with nanospray desorption electrospray ionization and direct infusion electrospray ionization were utilized to compare the organic composition of the particle and cloud water samples, respectively. Isoprene and monoterpene-derived organosulfates and oligomers were identified in both the particles and cloud water, showing the significant influencemore » of biogenic volatile organic compound oxidation above the forested region. While the average O:C ratios of the organic compounds were similar between the atmospheric particle and cloud water samples, the chemical composition of these samples was quite different. Specifically, hydrolysis of organosulfates and formation of nitrogen-containing compounds were observed for the cloud water when compared to the atmospheric particle samples, demonstrating that cloud processing changes the composition of organic aerosol.« less

EDITORIAL: Aerosol cloud interactions—a challenge for measurements and modeling at the cutting edge of cloud climate interactions

NASA Astrophysics Data System (ADS)

Spichtinger, Peter; Cziczo, Daniel J.

2008-04-01

Research in aerosol properties and cloud characteristics have historically been considered two separate disciplines within the field of atmospheric science. As such, it has been uncommon for a single researcher, or even research group, to have considerable expertise in both subject areas. The recent attention paid to global climate change has shown that clouds can have a considerable effect on the Earth's climate and that one of the most uncertain aspects in their formation, persistence, and ultimate dissipation is the role played by aerosols. This highlights the need for researchers in both disciplines to interact more closely than they have in the past. This is the vision behind this focus issue of Environmental Research Letters. Certain interactions between aerosols and clouds are relatively well studied and understood. For example, it is known that an increase in the aerosol concentration will increase the number of droplets in warm clouds, decrease their average size, reduce the rate of precipitation, and extend the lifetime. Other effects are not as well known. For example, persistent ice super-saturated conditions are observed in the upper troposphere that appear to exceed our understanding of the conditions required for cirrus cloud formation. Further, the interplay of dynamics versus effects purely attributed to aerosols remains highly uncertain. The purpose of this focus issue is to consider the current state of knowledge of aerosol/cloud interactions, to define the contemporary uncertainties, and to outline research foci as we strive to better understand the Earth's climate system. This focus issue brings together laboratory experiments, field data, and model studies. The authors address issues associated with warm liquid water, cold ice, and intermediate temperature mixed-phase clouds. The topics include the uncertainty associated with the effect of black carbon and organics, aerosol types of anthropogenic interest, on droplet and ice formation. Phases of water which have not yet been fully defined, for example cubic ice, are considered. The impact of natural aerosols on clouds, for example mineral dust, is also discussed, as well as other natural but highly sensitive effects such as the Wegener Bergeron Findeisen process. It is our belief that this focus issue represents a leap forward not only in reducing the uncertainty associated with the interaction of aerosols and clouds but also a new link between groups that must work together to continue progress in this important area of climate science. Focus on Aerosol Cloud Interactions Contents The articles below represent the first accepted contributions and further additions will appear in the near future. The global influence of dust mineralogical composition on heterogeneous ice nucleation in mixed-phase clouds C Hoose, U Lohmann, R Erdin and I Tegen Ice formation via deposition nucleation on mineral dust and organics: dependence of onset relative humidity on total particulate surface area Zamin A Kanji, Octavian Florea and Jonathan P D Abbatt The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol cloud interactions in multiscale modeling framework models: tracer transport results William I Gustafson Jr, Larry K Berg, Richard C Easter and Steven J Ghan Cloud effects from boreal forest fire smoke: evidence for ice nucleation from polarization lidar data and cloud model simulations Kenneth Sassen and Vitaly I Khvorostyanov The effect of organic coating on the heterogeneous ice nucleation efficiency of mineral dust aerosols O Möhler, S Benz, H Saathoff, M Schnaiter, R Wagner, J Schneider, S Walter, V Ebert and S Wagner Enhanced formation of cubic ice in aqueous organic acid droplets Benjamin J Murray Quantification of water uptake by soot particles O B Popovicheva, N M Persiantseva, V Tishkova, N K Shonija and N A Zubareva Meridional gradients of light absorbing carbon over northern Europe D Baumgardner, G Kok, M Krämer and F Weidle

Validation of satellite retrievals of cloud microsphysics and liquid water path using observations from FIRE

NASA Technical Reports Server (NTRS)

Rossow, W.; White, A.; Han, Q.; Welch, R.; Chou, J.

1995-01-01

Cloud effective radii (r(sub e)) and cloud liquid water path (LWP) are derived from ISCCP spatially sampled satellite data and validated with ground-based pyranometer and microwave radiometer measurements taken on San Nicolas Island during the 1987 FIRE IFO. Values of r(sub e) derived from the ISCCP data are also compared to values retrieved by a hybrid method that uses the combination of LWP derived from microwave measurement and optical thickness derived from GOES data. The results show that there is significant variability in cloud properties over a 100 km x 80 km area and that the values at San Nicolas Island are not necessarily representative of the surrounding cloud field. On the other hand, even though there were large spatial variations in optical depth, the r(sub e) values remained relatively constant (with sigma less than or equal to 2-3 microns in most cases) in the marine stratocumulus. Furthermore, values of r(sub e) derived from the upper portion of the cloud generally are representative of the entire stratiform cloud. When LWP values are less than 100 g m(exp -2), then LWP values derived from ISCCP data agree well with those values estimated from ground-based microwave measurements. In most cases LWP differences were less than 20 g m(exp -2). However, when LWP values become large (e.g., greater than or equal to 200 g m(exp -2)), then relative differences may be as large as 50%- 100%. There are two reasons for this discrepancy in the large LWP clouds: (1) larger vertical inhomogeneities in precipitating clouds and (2) sampling errors on days of high spatial variability of cloud optical thicknesses. Variations of r(sub e) in stratiform clouds may indicate drizzle: clouds with droplet sizes larger than 15 microns appear to be associated with drizzling, while those less than 10 microns are indicative of nonprecipitating clouds. Differences in r(sub e) values between the GOES and ISCCP datasets are found to be 0.16 +/- 0.98 micron.

CGILS Phase 2 LES intercomparison of response of subtropical marine low cloud regimes to CO 2 quadrupling and a CMIP3 composite forcing change: Large eddy simulation of cloud feedbacks

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

Blossey, Peter N.; Bretherton, Christopher S.; Cheng, Anning

We extended Phase 1 of the CGILS large-eddy simulation (LES) intercomparison in order to understand if subtropical marine boundary-layer clouds respond to idealized climate perturbations consistently in six LES models. Here the responses to quadrupled carbon dioxide (“fast adjustment”) and to a composite climate perturbation representative of CMIP3 multimodel mean 2×CO 2 near-equilibrium conditions are analyzed. As in Phase 1, the LES is run to equilibrium using specified steady summertime forcings representative of three locations in the Northeast Pacific Ocean in shallow well-mixed stratocumulus, decoupled stratocumulus, and shallow cumulus cloud regimes. Our results are generally consistent with a single-LES studymore » of Bretherton et al. (2013) on which this intercomparison was based. Both quadrupled CO 2 and the composite climate perturbation result in less cloud and a shallower boundary layer for all models in well-mixed stratocumulus and for all but a single LES in decoupled stratocumulus and shallow cumulus, corroborating similar findings from global climate models (GCMs). For both perturbations, the amount of cloud reduction varies across the models, but there is less intermodel scatter than in GCMs. Furthermore, the cloud radiative effect changes are much larger in the stratocumulus-capped regimes than in the shallow cumulus regime, for which precipitation buffering may damp the cloud response. In the decoupled stratocumulus and cumulus regimes, both the CO 2 increase and CMIP3 perturbations reduce boundary-layer decoupling, due to the shallowing of inversion height.« less

CGILS Phase 2 LES intercomparison of response of subtropical marine low cloud regimes to CO 2 quadrupling and a CMIP3 composite forcing change: Large eddy simulation of cloud feedbacks

DOE PAGES

Blossey, Peter N.; Bretherton, Christopher S.; Cheng, Anning; ...

2016-10-27

We extended Phase 1 of the CGILS large-eddy simulation (LES) intercomparison in order to understand if subtropical marine boundary-layer clouds respond to idealized climate perturbations consistently in six LES models. Here the responses to quadrupled carbon dioxide (“fast adjustment”) and to a composite climate perturbation representative of CMIP3 multimodel mean 2×CO 2 near-equilibrium conditions are analyzed. As in Phase 1, the LES is run to equilibrium using specified steady summertime forcings representative of three locations in the Northeast Pacific Ocean in shallow well-mixed stratocumulus, decoupled stratocumulus, and shallow cumulus cloud regimes. Our results are generally consistent with a single-LES studymore » of Bretherton et al. (2013) on which this intercomparison was based. Both quadrupled CO 2 and the composite climate perturbation result in less cloud and a shallower boundary layer for all models in well-mixed stratocumulus and for all but a single LES in decoupled stratocumulus and shallow cumulus, corroborating similar findings from global climate models (GCMs). For both perturbations, the amount of cloud reduction varies across the models, but there is less intermodel scatter than in GCMs. Furthermore, the cloud radiative effect changes are much larger in the stratocumulus-capped regimes than in the shallow cumulus regime, for which precipitation buffering may damp the cloud response. In the decoupled stratocumulus and cumulus regimes, both the CO 2 increase and CMIP3 perturbations reduce boundary-layer decoupling, due to the shallowing of inversion height.« less

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

Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica

Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOVmore » ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.« less

Security model for VM in cloud

NASA Astrophysics Data System (ADS)

Kanaparti, Venkataramana; Naveen K., R.; Rajani, S.; Padmvathamma, M.; Anitha, C.

2013-03-01

Cloud computing is a new approach emerged to meet ever-increasing demand for computing resources and to reduce operational costs and Capital Expenditure for IT services. As this new way of computation allows data and applications to be stored away from own corporate server, it brings more issues in security such as virtualization security, distributed computing, application security, identity management, access control and authentication. Even though Virtualization forms the basis for cloud computing it poses many threats in securing cloud. As most of Security threats lies at Virtualization layer in cloud we proposed this new Security Model for Virtual Machine in Cloud (SMVC) in which every process is authenticated by Trusted-Agent (TA) in Hypervisor as well as in VM. Our proposed model is designed to with-stand attacks by unauthorized process that pose threat to applications related to Data Mining, OLAP systems, Image processing which requires huge resources in cloud deployed on one or more VM's.

Climate Simulations from Super-parameterized and Conventional General Circulation Models with a Third-order Turbulence Closure

NASA Astrophysics Data System (ADS)

Xu, Kuan-Man; Cheng, Anning

2014-05-01

A high-resolution cloud-resolving model (CRM) embedded in a general circulation model (GCM) is an attractive alternative for climate modeling because it replaces all traditional cloud parameterizations and explicitly simulates cloud physical processes in each grid column of the GCM. Such an approach is called "Multiscale Modeling Framework." MMF still needs to parameterize the subgrid-scale (SGS) processes associated with clouds and large turbulent eddies because circulations associated with planetary boundary layer (PBL) and in-cloud turbulence are unresolved by CRMs with horizontal grid sizes on the order of a few kilometers. A third-order turbulence closure (IPHOC) has been implemented in the CRM component of the super-parameterized Community Atmosphere Model (SPCAM). IPHOC is used to predict (or diagnose) fractional cloudiness and the variability of temperature and water vapor at scales that are not resolved on the CRM's grid. This model has produced promised results, especially for low-level cloud climatology, seasonal variations and diurnal variations (Cheng and Xu 2011, 2013a, b; Xu and Cheng 2013a, b). Because of the enormous computational cost of SPCAM-IPHOC, which is 400 times of a conventional CAM, we decided to bypass the CRM and implement the IPHOC directly to CAM version 5 (CAM5). IPHOC replaces the PBL/stratocumulus, shallow convection, and cloud macrophysics parameterizations in CAM5. Since there are large discrepancies in the spatial and temporal scales between CRM and CAM5, IPHOC used in CAM5 has to be modified from that used in SPCAM. In particular, we diagnose all second- and third-order moments except for the fluxes. These prognostic and diagnostic moments are used to select a double-Gaussian probability density function to describe the SGS variability. We also incorporate a diagnostic PBL height parameterization to represent the strong inversion above PBL. The goal of this study is to compare the simulation of the climatology from these three models (CAM5, CAM5-IPHOC and SPCAM-IPHOC), with emphasis on low-level clouds and precipitation. Detailed comparisons of scatter diagrams among the monthly-mean low-level cloudiness, PBL height, surface relative humidity and lower tropospheric stability (LTS) reveal the relative strengths and weaknesses for five coastal low-cloud regions among the three models. Observations from CloudSat and CALIPSO and ECMWF Interim reanalysis are used as the truths for the comparisons. We found that the standard CAM5 underestimates cloudiness and produces small cloud fractions at low PBL heights that contradict with observations. CAM5-IPHOC tends to overestimate low clouds but the ranges of LTS and PBL height variations are most realistic. SPCAM-IPHOC seems to produce most realistic results with relatively consistent results from one region to another. Further comparisons with other atmospheric environmental variables will be helpful to reveal the causes of model deficiencies so that SPCAM-IPHOC results will provide guidance to the other two models.

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

Matthew R. Kumjian; Giangrande, Scott E.; Mishra, Subashree

Polarimetric radar observations increasingly are used to understand cloud microphysical processes, which is critical for improving their representation in cloud and climate models. In particular, there has been recent focus on improving representations of ice collection processes (e.g., aggregation, riming), as these influence precipitation rate, heating profiles, and ultimately cloud life cycles. However, distinguishing these processes using conventional polarimetric radar observations is difficult, as they produce similar fingerprints. This necessitates improved analysis techniques and integration of complementary data sources. Furthermore, the Midlatitude Continental Convective Clouds Experiment (MC3E) provided such an opportunity.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

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

New Insight into Polar Stratospheric Cloud Processes from A-Train Observations

NASA Astrophysics Data System (ADS)

Pitts, M. C.; Poole, L. R.

2016-12-01

Polar stratospheric clouds (PSCs) play essential roles in the chemical depletion of stratospheric ozone at high latitudes. Heterogeneous reactions occurring on PSC particles, primarily supercooled ternary (H2SO4-H2O-HNO3) solution (STS) droplets, convert stable chlorine reservoir species to highly reactive ozone-destructive forms. Also, sedimentation and evaporation of large nitric acid trihydrate (NAT) particles irreversibly redistributes odd nitrogen and prolongs ozone depletion by slowing the reformation of stable chlorine reservoirs. Even after three decades of research, significant gaps in our understanding of PSC processes still exist, particularly concerning NAT nucleation and the extent to which chlorine is activated on cold background aerosol prior to PSC formation. These uncertainties limit our ability to represent PSCs accurately in global models and call into question predictions of ozone recovery in a changing climate. PSC observations from the A-Train satellite constellation have stimulated a number of new research activities that have both extended and challenged our knowledge of PSC processes and modeling capabilities. Specifically, the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite is providing information on PSC morphology and composition in unprecedented detail, while the Microwave Limb Sounder (MLS) on the Aura satellite is providing nearly coincident measurements of gas-phase HNO3 and H2O, the major constituents of all PSC particles. The combined analyses of these datasets enable better PSC composition discrimination and provide valuable new insight into processes such as PSC-catalyzed chlorine activation and PSC particle growth kinetics. The more than ten years of CALIOP and MLS measurements have uniquely captured the primary aspects of the seasonal and multi-year variability of PSCs in the Arctic and Antarctic and are enabling the development of a state-of-the-art reference PSC data record and climatology which can be utilized to test current and future global models. In this paper, we will illustrate key features of this evolving PSC climatology and highlight recent significant findings with regard to PSC processes in the Arctic and Antarctic.

Towards Cloud-Resolving European-Scale Climate Simulations using a fully GPU-enabled Prototype of the COSMO Regional Model

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Cumming, Benjamin; Lapillonne, Xavier; Gysi, Tobias; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph

2014-05-01

The representation of moist convection is a major shortcoming of current global and regional climate models. State-of-the-art global models usually operate at grid spacings of 10-300 km, and therefore cannot fully resolve the relevant upscale and downscale energy cascades. Therefore parametrization of the relevant sub-grid scale processes is required. Several studies have shown that this approach entails major uncertainties for precipitation processes, which raises concerns about the model's ability to represent precipitation statistics and associated feedback processes, as well as their sensitivities to large-scale conditions. Further refining the model resolution to the kilometer scale allows representing these processes much closer to first principles and thus should yield an improved representation of the water cycle including the drivers of extreme events. Although cloud-resolving simulations are very useful tools for climate simulations and numerical weather prediction, their high horizontal resolution and consequently the small time steps needed, challenge current supercomputers to model large domains and long time scales. The recent innovations in the domain of hybrid supercomputers have led to mixed node designs with a conventional CPU and an accelerator such as a graphics processing unit (GPU). GPUs relax the necessity for cache coherency and complex memory hierarchies, but have a larger system memory-bandwidth. This is highly beneficial for low compute intensity codes such as atmospheric stencil-based models. However, to efficiently exploit these hybrid architectures, climate models need to be ported and/or redesigned. Within the framework of the Swiss High Performance High Productivity Computing initiative (HP2C) a project to port the COSMO model to hybrid architectures has recently come to and end. The product of these efforts is a version of COSMO with an improved performance on traditional x86-based clusters as well as hybrid architectures with GPUs. We present our redesign and porting approach as well as our experience and lessons learned. Furthermore, we discuss relevant performance benchmarks obtained on the new hybrid Cray XC30 system "Piz Daint" installed at the Swiss National Supercomputing Centre (CSCS), both in terms of time-to-solution as well as energy consumption. We will demonstrate a first set of short cloud-resolving climate simulations at the European-scale using the GPU-enabled COSMO prototype and elaborate our future plans on how to exploit this new model capability.

Bubbly Little Star

NASA Technical Reports Server (NTRS)

2007-01-01

In this processed Spitzer Space Telescope image, baby star HH 46/47 can be seen blowing two massive 'bubbles.' The star is 1,140 light-years away from Earth.

The infant star can be seen as a white spot toward the center of the Spitzer image. The two bubbles are shown as hollow elliptical shells of bluish-green material extending from the star. Wisps of green in the image reveal warm molecular hydrogen gas, while the bluish tints are formed by starlight scattered by surrounding dust.

These bubbles formed when powerful jets of gas, traveling at 200 to 300 kilometers per second, or about 120 to 190 miles per second, smashed into the cosmic cloud of gas and dust that surrounds HH 46/47. The red specks at the end of each bubble show the presence of hot sulfur and iron gas where the star's narrow jets are currently crashing head-on into the cosmic cloud's gas and dust material.

Whenever astronomers observe a star, or snap a stellar portrait, through the lens of any telescope, they know that what they are seeing is slightly blurred. To clear up the blurring in Spitzer images, astronomers at the Jet Propulsion Laboratory developed an image processing technique for Spitzer called Hi-Res deconvolution.

This process reduces blurring and makes the image sharper and cleaner, enabling astronomers to see the emissions around forming stars in greater detail. When scientists applied this image processing technique to the Spitzer image of HH 46/47, they were able to see winds from the star and jets of gas that are carving the celestial bubbles.

This infrared image is a three-color composite, with data at 3.6 microns represented in blue, 4.5 and 5.8 microns shown in green, and 24 microns represented as red.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

The cloud-phase feedback in the Super-parameterized Community Earth System Model

NASA Astrophysics Data System (ADS)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

Research of MPPT for photovoltaic generation based on two-dimensional cloud model

NASA Astrophysics Data System (ADS)

Liu, Shuping; Fan, Wei

2013-03-01

The cloud model is a mathematical representation to fuzziness and randomness in linguistic concepts. It represents a qualitative concept with expected value Ex, entropy En and hyper entropy He, and integrates the fuzziness and randomness of a linguistic concept in a unified way. This model is a new method for transformation between qualitative and quantitative in the knowledge. This paper is introduced MPPT (maximum power point tracking, MPPT) controller based two- dimensional cloud model through analysis of auto-optimization MPPT control of photovoltaic power system and combining theory of cloud model. Simulation result shows that the cloud controller is simple and easy, directly perceived through the senses, and has strong robustness, better control performance.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Cloud Base Height Measurements at Manila Observatory: Initial Results from Constructed Paired Sky Imaging Cameras

NASA Astrophysics Data System (ADS)

Lagrosas, N.; Tan, F.; Antioquia, C. T.

2014-12-01

Fabricated all sky imagers are efficient and cost effective instruments for cloud detection and classification. Continuous operation of this instrument can result in the determination of cloud occurrence and cloud base heights for the paired system. In this study, a fabricated paired sky imaging system - consisting two commercial digital cameras (Canon Powershot A2300) enclosed in weatherproof containers - is developed in Manila Observatory for the purpose of determining cloud base heights at the Manila Observatory area. One of the cameras is placed on the rooftop of Manila Observatory and the other is placed on the rooftop of the university dormitory, 489m from the first camera. The cameras are programmed to simultaneously gather pictures every 5 min. Continuous operation of these cameras were implemented since the end of May of 2014 but data collection started end of October 2013. The data were processed following the algorithm proposed by Kassianov et al (2005). The processing involves the calculation of the merit function that determines the area of overlap of the two pictures. When two pictures are overlapped, the minimum of the merit function corresponds to the pixel column positions where the pictures have the best overlap. In this study, pictures of overcast sky prove to be difficult to process for cloud base height and were excluded from processing. The figure below shows the initial results of the hourly average of cloud base heights from data collected from November 2013 to July 2014. Measured cloud base heights ranged from 250m to 1.5km. These are the heights of cumulus and nimbus clouds that are dominant in this part of the world. Cloud base heights are low in the early hours of the day indicating low convection process during these times. However, the increase in the convection process in the atmosphere can be deduced from higher cloud base heights in the afternoon. The decrease of cloud base heights after 15:00 follows the trend of decreasing solar energy in the atmosphere after this time. The results show the potential of these instruments to determine cloud base heights on prolonged time intervals. The continuous operation of these instruments is implemented to gather seasonal variation of cloud base heights in this part of the world and to add to the much-needed dataset for future climate studies in Manila Observatory.

Developing large-scale forcing data for single-column and cloud-resolving models from the Mixed-Phase Arctic Cloud Experiment

DOE PAGES

Xie, Shaocheng; Klein, Stephen A.; Zhang, Minghua; ...

2006-10-05

[1] This study represents an effort to develop Single-Column Model (SCM) and Cloud-Resolving Model large-scale forcing data from a sounding array in the high latitudes. An objective variational analysis approach is used to process data collected from the Atmospheric Radiation Measurement Program (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE), which was conducted over the North Slope of Alaska in October 2004. In this method the observed surface and top of atmosphere measurements are used as constraints to adjust the sounding data from M-PACE in order to conserve column-integrated mass, heat, moisture, and momentum. Several important technical and scientific issues related tomore » the data analysis are discussed. It is shown that the analyzed data reasonably describe the dynamic and thermodynamic features of the Arctic cloud systems observed during M-PACE. Uncertainties in the analyzed forcing fields are roughly estimated by examining the sensitivity of those fields to uncertainties in the upper-air data and surface constraints that are used in the analysis. Impacts of the uncertainties in the analyzed forcing data on SCM simulations are discussed. Results from the SCM tests indicate that the bulk features of the observed Arctic cloud systems can be captured qualitatively well using the forcing data derived in this study, and major model errors can be detected despite the uncertainties that exist in the forcing data as illustrated by the sensitivity tests. Lastly, the possibility of using the European Center for Medium-Range Weather Forecasts analysis data to derive the large-scale forcing over the Arctic region is explored.« less

ULTRAVIOLET ESCAPE FRACTIONS FROM GIANT MOLECULAR CLOUDS DURING EARLY CLUSTER FORMATION

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

Howard, Corey; Pudritz, Ralph; Klessen, Ralf

2017-01-01

The UV photon escape fraction from molecular clouds is a key parameter for understanding the ionization of the interstellar medium and extragalactic processes such as cosmic reionization. We present the ionizing photon flux and the corresponding photon escape fraction ( f {sub esc}) arising as a consequence of star cluster formation in a turbulent, 10{sup 6} M {sub ⊙} giant molecular cloud, simulated using the code FLASH. We make use of sink particles to represent young, star-forming clusters coupled with a radiative transfer scheme to calculate the emergent UV flux. We find that the ionizing photon flux across the cloudmore » boundary is highly variable in time and space due to the turbulent nature of the intervening gas. The escaping photon fraction remains at ∼5% for the first 2.5 Myr, followed by two pronounced peaks at 3.25 and 3.8 Myr with a maximum f {sub esc} of 30% and 37%, respectively. These peaks are due to the formation of large H ii regions that expand into regions of lower density, some of which reaching the cloud surface. However, these phases are short-lived, and f {sub esc} drops sharply as the H ii regions are quenched by the central cluster passing through high-density material due to the turbulent nature of the cloud. We find an average f {sub esc} of 15% with factor of two variations over 1 Myr timescales. Our results suggest that assuming a single value for f {sub esc} from a molecular cloud is in general a poor approximation, and that the dynamical evolution of the system leads to large temporal variation.« less

Aerosol properties and their impacts on surface CCN at the ARM Southern Great Plains site during the 2011 Midlatitude Continental Convective Clouds Experiment

NASA Astrophysics Data System (ADS)

Logan, Timothy; Dong, Xiquan; Xi, Baike

2018-02-01

Aerosol particles are of particular importance because of their impacts on cloud development and precipitation processes over land and ocean. Aerosol properties as well as meteorological observations from the Department of Energy Atmospheric Radiation Measurement (ARM) platform situated in the Southern Great Plains (SGP) are utilized in this study to illustrate the dependence of continental cloud condensation nuclei (CCN) number concentration ( N CCN) on aerosol type and transport pathways. ARM-SGP observations from the 2011 Midlatitude Continental Convective Clouds Experiment field campaign are presented in this study and compared with our previous work during the 2009-10 Clouds, Aerosol, and Precipitation in the Marine Boundary Layer field campaign over the current ARM Eastern North Atlantic site. Northerly winds over the SGP reflect clean, continental conditions with aerosol scattering coefficient ( σ sp) values less than 20 Mm-1 and N CCN values less than 100 cm-3. However, southerly winds over the SGP are responsible for the observed moderate to high correlation ( R) among aerosol loading ( σ sp < 60 Mm-1) and N CCN, carbonaceous chemical species (biomass burning smoke), and precipitable water vapor. This suggests a common transport mechanism for smoke aerosols and moisture via the Gulf of Mexico, indicating a strong dependence on air mass type. NASA MERRA-2 reanalysis aerosol and chemical data are moderately to highly correlated with surface ARM-SGP data, suggesting that this facility can represent surface aerosol conditions in the SGP, especially during strong aerosol loading events that transport via the Gulf of Mexico. Future long-term investigations will help to understand the seasonal influences of air masses on aerosol, CCN, and cloud properties over land in comparison to over ocean.

Glacial Inception in north-east Canada: The Role of Topography and Clouds

NASA Astrophysics Data System (ADS)

Birch, Leah; Tziperman, Eli; Cronin, Timothy

2016-04-01

Over the past 0.8 million years, ice ages have dominated Earth's climate on a 100 thousand year cycle. Interglacials were brief, sometimes lasting only a few thousand years, leading to the next inception. Currently, state-of-the-art global climate models (GCMs) are incapable of simulating the transition of Earth's climate from interglacial to glaciated. We hypothesize that this failure may be related to their coarse spatial resolution, which does not allow resolving the topography of inception areas, and their parameterized representation of clouds and atmospheric convection. To better understand the small scale topographic and cloud processes mis-represented by GCMs, we run the Weather Research and Forecasting model (WRF), which is a regional, cloud-resolving atmospheric model capable of a realistic simulation of the regional mountain climate and therefore of surface ice and snow mass balance. We focus our study on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred at 115kya. We examine the sensitivity of mountain glaciers to Milankovitch Forcing, topography, and meteorology, while observing impacts of a cloud resolving model. We first verify WRF's ability to simulate present day climate in the region surrounding the Penny Ice Cap, and then investigate how a GCM-like biased representation of topography affects sensitivity of this mountain glacier to Milankovitch forcing. Our results show the possibility of ice cap growth on an initially snow-free landscape with realistic topography and insolation values from the last glacial inception. Whereas, smoothed topography as seen in GCMs has a negative surface mass balance, even with the relevant orbital parameter configuration. We also explore the surface mass balance feedbacks from an initially ice-covered Baffin Island and discuss the role of clouds and convection.

Blowing in the Milky Way Wind: Neutral Hydrogen Clouds Tracing the Galactic Nuclear Outflow

NASA Astrophysics Data System (ADS)

Di Teodoro, Enrico M.; McClure-Griffiths, N. M.; Lockman, Felix J.; Denbo, Sara R.; Endsley, Ryan; Ford, H. Alyson; Harrington, Kevin

2018-03-01

We present the results of a new sensitive survey of neutral hydrogen above and below the Galactic Center with the Green Bank Telescope. The observations extend up to Galactic latitude | b| < 10^\\circ with an effective angular resolution of 9.‧5 and an average rms brightness temperature noise of 40 mK in a 1 {km} {{{s}}}-1 channel. The survey reveals the existence of a population of anomalous high-velocity clouds extending up to heights of about 1.5 kpc from the Galactic plane and showing no signature of Galactic rotation. These clouds have local standard of rest velocities | {V}LSR}| ≲ 360 {km} {{{s}}}-1, and assuming a Galactic Center origin, they have sizes of a few tens of parsec and neutral hydrogen masses spanning 10{--}{10}5 {M}ȯ . Accounting for selection effects, the cloud population is symmetric in longitude, latitude, and V LSR. We model the cloud kinematics in terms of an outflow expanding from the Galactic Center and find the population consistent with being material moving with radial velocity {V}{{w}}≃ 330 {km} {{{s}}}-1 distributed throughout a bicone with opening angle α > 140^\\circ . This simple model implies an outflow luminosity {L}{{w}}> 3× {10}40 erg s‑1 over the past 10 Myr, consistent with star formation feedback in the inner region of the Milky Way, with a cold gas mass-loss rate ≲ 0.1 {{M}ȯ {yr}}-1. These clouds may represent the cold gas component accelerated in the nuclear wind driven by our Galaxy, although some of the derived properties challenge current theoretical models of the entrainment process.

Further developments in cloud statistics for computer simulations

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Ground-based weather radar remote sensing of volcanic ash explosive eruptions

NASA Astrophysics Data System (ADS)

Marzano, F. S.; Marchiotto, S.; Barbieri, S.; Giuliani, G.; Textor, C.; Schneider, D. J.

2009-04-01

The explosive eruptions of active volcanoes with a consequent formation of ash clouds represent a severe threat in several regions of the urbanized world. During a Plinian or a sub-Plinian eruption the injection of large amounts of fine and coarse rock fragments and corrosive gases into the troposphere and lower stratosphere is usually followed by a long lasting ashfall which can cause a variety of damages. Volcanic ash clouds are an increasing hazard to aviation safety because of growing air traffic volumes that use more efficient and susceptible jet engines. Real-time and areal monitoring of a volcano eruption, in terms of its intensity and dynamics, is not always possible by conventional visual inspections, especially during worse visibility periods which are quite common during eruption activity. Remote sensing techniques both from ground and from space represent unique tools to be exploited. In this respect, microwave weather radars can gather three-dimensional information of atmospheric scattering volumes up several hundreds of kilometers, in all weather conditions, at a fairly high spatial resolution (less than a kilometer) and with a repetition cycle of few minutes. Ground-based radar systems represent one of the best methods for determining the height and volume of volcanic eruption clouds. Single-polarization Doppler radars can measure horizontally-polarized power echo and Doppler shift from which ash content and radial velocity can be, in principle, extracted. In spite of these potentials, there are still several open issues about microwave weather radar capabilities to detect and quantitatively retrieve ash cloud parameters. A major issue is related to the aggregation of volcanic ash particles within the eruption column of explosive eruptions which has been observed at many volcanoes. It influences the residence time of ash in the atmosphere and the radiative properties of the "umbrella" cloud. Numerical experiments are helpful to explore processes occurring in the eruption column. In this study we use the plume model ATHAM (Active Tracer High Resolution Atmospheric Model) to investigate, in both time and space, processes leading to particle aggregation in the eruption column. In this work a set of numerical simulations of radar reflectivity is performed with the ATHAM model, under the same experimental conditions except for the initial size distribution, i.e. varying the radii of average mass of the two particle dimension modes. A sensitivity analysis is carried out to evaluate the possible impact of aggregate particles on microwave radar reflectivity. It is shown how dimension, composition, temperature and mass concentration are the main characteristics of eruptive cloud particles that contribute to determine different radar reflectivity responses. In order to evaluate Rayleigh scattering approximation accuracy, the ATHAM simulations of radar reflectivity are used to compare in a detailed way the Mie and Rayleigh scattering regimes at S-, C- and X-band. The relationship between radar reflectivity factor and ash concentration has been statistically derived for the various particle classes by applying a new radar reflectivity microphysical model, which was developed starting from results of numerical experiments performed with plume model ATHAM. The ash retrieval physical-statistical algorithm is based on the backscattering microphysical model of volcanic cloud particles, used within a Bayesian classification and optimal regression algorithm. In order to illustrate the potential of this microwave active remote sensing technique, the case study of the eruption of Augustine volcano in Alaska in January 2006 is described. This event was the first time that a significant volcanic eruption was observed within the nominal range of a WSR-88D. The radar data, in conjunction with pilot reports, proved to be crucial in analyzing the height and movement of volcanic ash clouds during and immediately following each eruptive event. This data greatly aided National Weather Service meteorologists in the issuance of timely and accurate warning and advisory products to aviation, public, and marine interests. An application of the retrieval technique has been shown, taking into consideration the eruption of the Augustine volcano. Volume scan data from the NEXRAD WSR-88D S-band radar, which are located 190 km from the volcano vent, are processed to identify and estimate the particles concentration in an automatic fashion. The evolution of the Augustine Vulcanian eruption is discussed in terms of radar measurements products, pointing out the unique features, the current limitations and future improvements of radar remote sensing of volcanic plumes.

Hyperspectrally-Resolved Surface Emissivity Derived Under Optically Thin Clouds

NASA Technical Reports Server (NTRS)

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

2010-01-01

Surface spectral emissivity derived from current and future satellites can and will reveal critical information about the Earth s ecosystem and land surface type properties, which can be utilized as a means of long-term monitoring of global environment and climate change. Hyperspectrally-resolved surface emissivities are derived with an algorithm utilizes a combined fast radiative transfer model (RTM) with a molecular RTM and a cloud RTM accounting for both atmospheric absorption and cloud absorption/scattering. Clouds are automatically detected and cloud microphysical parameters are retrieved; and emissivity is retrieved under clear and optically thin cloud conditions. This technique separates surface emissivity from skin temperature by representing the emissivity spectrum with eigenvectors derived from a laboratory measured emissivity database; in other words, using the constraint as a means for the emissivity to vary smoothly across atmospheric absorption lines. Here we present the emissivity derived under optically thin clouds in comparison with that under clear conditions.

Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.

A short overview of the microbial population in clouds: Potential roles in atmospheric chemistry and nucleation processes

NASA Astrophysics Data System (ADS)

Delort, Anne-Marie; Vaïtilingom, Mickael; Amato, Pierre; Sancelme, Martine; Parazols, Marius; Mailhot, Gilles; Laj, Paolo; Deguillaume, Laurent

2010-11-01

Recent studies showed that living microorganisms, including bacteria, fungi and yeasts, are present in the atmospheric water phase (fog and clouds) and their role in chemical processes may have been underestimated. At the interface between atmospheric science and microbiology, information about this field of science suffers from the fact that not all recent findings are efficiently conveyed to both scientific communities. The purpose of this paper is therefore to provide a short overview of recent work linked to living organisms in the atmospheric water phase, from their activation to cloud droplets and ice crystal, to their potential impact on atmospheric chemical processes. This paper is focused on the microorganisms present in clouds and on the role they could play in atmospheric chemistry and nucleation processes. First, the life cycle of microorganisms via the atmosphere is examined, including their aerosolization from sources, their integration into clouds and their wet deposition on the ground. Second, special attention is paid to the possible impacts of microorganisms on liquid and ice nucleation processes. Third, a short description of the microorganisms that have been found in clouds and their variability in numbers and diversity is presented, emphasizing some specific characteristics that could favour their occurrence in cloud droplets. In the last section, the potential role of microbial activity as an alternative route to photochemical reaction pathways in cloud chemistry is discussed.

Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

DOE PAGES

Chen, Ying; Zhang, Yang; Fan, Jiwen; ...

2015-08-18

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011

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

Chen, Ying; Zhang, Yang; Fan, Jiwen

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

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

Chen, Ying; Zhang, Yang; Fan, Jiwen

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Li, Xiao-Fan; Sui, C.-H.; Lau, K.-M.; Tao, W.-K.

2004-01-01

Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.

Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

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

Hughes, Michael J.; Hayes, Daniel J

2014-01-01

Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for cloudsmore » (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.« less

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

NASA Technical Reports Server (NTRS)

Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Matsui, Toshihisa; Li, J.-L.; Mohr, Karen I.; Skofronick-Jackson, Gail M.; Peters-Lidard, Christa D.

2016-01-01

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

Min-Cut Based Segmentation of Airborne LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Ural, S.; Shan, J.

2012-07-01

Introducing an organization to the unstructured point cloud before extracting information from airborne lidar data is common in many applications. Aggregating the points with similar features into segments in 3-D which comply with the nature of actual objects is affected by the neighborhood, scale, features and noise among other aspects. In this study, we present a min-cut based method for segmenting the point cloud. We first assess the neighborhood of each point in 3-D by investigating the local geometric and statistical properties of the candidates. Neighborhood selection is essential since point features are calculated within their local neighborhood. Following neighborhood determination, we calculate point features and determine the clusters in the feature space. We adapt a graph representation from image processing which is especially used in pixel labeling problems and establish it for the unstructured 3-D point clouds. The edges of the graph that are connecting the points with each other and nodes representing feature clusters hold the smoothness costs in the spatial domain and data costs in the feature domain. Smoothness costs ensure spatial coherence, while data costs control the consistency with the representative feature clusters. This graph representation formalizes the segmentation task as an energy minimization problem. It allows the implementation of an approximate solution by min-cuts for a global minimum of this NP hard minimization problem in low order polynomial time. We test our method with airborne lidar point cloud acquired with maximum planned post spacing of 1.4 m and a vertical accuracy 10.5 cm as RMSE. We present the effects of neighborhood and feature determination in the segmentation results and assess the accuracy and efficiency of the implemented min-cut algorithm as well as its sensitivity to the parameters of the smoothness and data cost functions. We find that smoothness cost that only considers simple distance parameter does not strongly conform to the natural structure of the points. Including shape information within the energy function by assigning costs based on the local properties may help to achieve a better representation for segmentation.

Atmospheric chemistry of carboxylic acids: microbial implication versus photochemistry

NASA Astrophysics Data System (ADS)

Vaïtilingom, M.; Charbouillot, T.; Deguillaume, L.; Maisonobe, R.; Parazols, M.; Amato, P.; Sancelme, M.; Delort, A.-M.

2011-02-01

Clouds are multiphasic atmospheric systems in which the dissolved organic compounds, dominated by carboxylic acids, are subject to multiple chemical transformations in the aqueous phase. Among them, solar radiation, by generating hydroxyl radicals (•OH), is considered as the main catalyzer of the reactivity of organic species in clouds. We investigated to which extent the active biomass existing in cloud water represents an alternative route to the chemical reactivity of carboxylic acids. Pure cultures of seventeen bacterial strains (Arthrobacter, Bacillus, Clavibacter, Frigoribacterium, Pseudomonas, Sphingomonas and Rhodococcus), previously isolated from cloud water and representative of the viable community of clouds were first individually incubated in two artificial bulk cloud water solutions at 17 °C and 5 °C. These solutions mimicked the chemical composition of cloud water from "marine" and "continental" air masses, and contained the major carboxylic acids existing in the cloud water (i.e. acetate, formate, succinate and oxalate). The concentrations of these carboxylic compounds were monitored over time and biodegradation rates were determined. In average, they ranged from 2 ×10-19 for succinate to 1 × 10-18 mol cell-1 s-1 for formate at 17 °C and from 4 × 10-20 for succinate to 6 × 10-19 mol cell-1 s-1 for formate at 5 °C, with no significant difference between "marine" and "continental" media. In parallel, irradiation experiments were also conducted in these two artificial media to compare biodegradation and photodegradation of carboxylic compounds. To complete this comparison, the photodegradation rates of carboxylic acids by •OH radicals were calculated from literature data. Inferred estimations suggested a significant participation of microbes to the transformation of carboxylic acids in cloud water, particularly for acetate and succinate (up to 90%). Furthermore, a natural cloud water sample was incubated (including its indigenous microflora); the rates of biodegradation were determined and compared to the photodegradation rates involving •OH radicals. The biodegradation rates in "natural" and "artificial" cloud water were in the same order of magnitude; this confirms the significant role of the active biomass in the aqueous reactivity of clouds.

Contrasting influences of aerosols on cloud properties during deficient and abundant monsoon years

PubMed Central

Patil, Nitin; Dave, Prashant; Venkataraman, Chandra

2017-01-01

Direct aerosol radiative forcing facilitates the onset of Indian monsoon rainfall, based on synoptic scale fast responses acting over timescales of days to a month. Here, we examine relationships between aerosols and coincident clouds over the Indian subcontinent, using observational data from 2000 to 2009, from the core monsoon region. Season mean and daily timescales were considered. The correlation analyses of cloud properties with aerosol optical depth revealed that deficient monsoon years were characterized by more frequent and larger decreases in cloud drop size and ice water path, but increases in cloud top pressure, with increases in aerosol abundance. The opposite was observed during abundant monsoon years. The correlations of greater aerosol abundance, with smaller cloud drop size, lower evidence of ice processes and shallower cloud height, during deficient rainfall years, imply cloud inhibition; while those with larger cloud drop size, greater ice processes and a greater cloud vertical extent, during abundant rainfall years, suggest cloud invigoration. The study establishes that continental aerosols over India alter cloud properties in diametrically opposite ways during contrasting monsoon years. The mechanisms underlying these effects need further analysis. PMID:28337991

Contrasting influences of aerosols on cloud properties during deficient and abundant monsoon years.

PubMed

Patil, Nitin; Dave, Prashant; Venkataraman, Chandra

2017-03-24

Direct aerosol radiative forcing facilitates the onset of Indian monsoon rainfall, based on synoptic scale fast responses acting over timescales of days to a month. Here, we examine relationships between aerosols and coincident clouds over the Indian subcontinent, using observational data from 2000 to 2009, from the core monsoon region. Season mean and daily timescales were considered. The correlation analyses of cloud properties with aerosol optical depth revealed that deficient monsoon years were characterized by more frequent and larger decreases in cloud drop size and ice water path, but increases in cloud top pressure, with increases in aerosol abundance. The opposite was observed during abundant monsoon years. The correlations of greater aerosol abundance, with smaller cloud drop size, lower evidence of ice processes and shallower cloud height, during deficient rainfall years, imply cloud inhibition; while those with larger cloud drop size, greater ice processes and a greater cloud vertical extent, during abundant rainfall years, suggest cloud invigoration. The study establishes that continental aerosols over India alter cloud properties in diametrically opposite ways during contrasting monsoon years. The mechanisms underlying these effects need further analysis.

A microphysical pathway analysis to investigate aerosol effects on convective clouds

NASA Astrophysics Data System (ADS)

Heikenfeld, Max; White, Bethan; Labbouz, Laurent; Stier, Philip

2017-04-01

The impact of aerosols on ice- and mixed-phase processes in convective clouds remains highly uncertain, which has strong implications for estimates of the role of aerosol-cloud interactions in the climate system. The wide range of interacting microphysical processes are still poorly understood and generally not resolved in global climate models. To understand and visualise these processes and to conduct a detailed pathway analysis, we have added diagnostic output of all individual process rates for number and mass mixing ratios to two commonly-used cloud microphysics schemes (Thompson and Morrison) in WRF. This allows us to investigate the response of individual processes to changes in aerosol conditions and the propagation of perturbations throughout the development of convective clouds. Aerosol effects on cloud microphysics could strongly depend on the representation of these interactions in the model. We use different model complexities with regard to aerosol-cloud interactions ranging from simulations with different levels of fixed cloud droplet number concentration (CDNC) as a proxy for aerosol, to prognostic CDNC with fixed modal aerosol distributions. Furthermore, we have implemented the HAM aerosol model in WRF-chem to also perform simulations with a fully interactive aerosol scheme. We employ a hierarchy of simulation types to understand the evolution of cloud microphysical perturbations in atmospheric convection. Idealised supercell simulations are chosen to present and test the analysis methods for a strongly confined and well-studied case. We then extend the analysis to large case study simulations of tropical convection over the Amazon rainforest. For both cases we apply our analyses to individually tracked convective cells. Our results show the impact of model uncertainties on the understanding of aerosol-convection interactions and have implications for improving process representation in models.

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

NASA Astrophysics Data System (ADS)

Cura, Rémi; Perret, Julien; Paparoditis, Nicolas

2017-05-01

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

Microphysical properties of cirrus clouds between 75°N and 25°S derived from extensive airborne in-situ observations

NASA Astrophysics Data System (ADS)

Krämer, Martina

2016-04-01

Numerous airborne field campaigns were performed in the last decades to record cirrus clouds microphysical properties. Beside the understanding of the processes of cirrus formation and evolution, an additional motivation for those studies is to provide a database to evaluate the representation of cirrus clouds in global climate models. This is of importance for an improved certainty of climate predictions, which are affected by the poor understanding of the microphysical processes of ice clouds (IPCC, 2013). To this end, the observations should ideally cover the complete respective parameter range and not be influenced by instrumental artifacts. However, due to the difficulties in measuring cirrus properties on fast-flying, high-altitude aircraft, some issues with respect to the measurements %evolved have arisen. In particular, concerns about the relative humidity in and around cirrus clouds and the ice crystal number concentrations were under discussion. Too high ice supersaturations as well as ice number concentrations were often reported. These issues have made more challenging the goal of compiling a large database using data from a suite of different instruments that were used on different campaigns. In this study, we have have addressed these challenges and compiled a large data set of cirrus clouds, sampled during eighteen field campaigns between 75°N and 25°S, representing measurements fulfilling the above mentioned requirements. The most recent campaigns were performed in 2014; namely, the ATTREX campaign with the research aircraft Global Hawk and the ML-CIRRUS and ACRIDICON campaigns with HALO. % The observations include ice water content (IWC: 130 hours of observations), ice crystal numbers (N_ice: 83 hours), ice crystal mean mass size (Rice: 83 hours) and relative humidity (RH_ice) in- and outside of cirrus clouds (78 and 140 hours). % We will present the parameters as PDFs versus temperature and derive medians and core ranges (including the most frequent observations) for each parameter. The new large data sets confirm the earlier results presented by Schiller et al. (JGR, 2008), Krämer et al. (ACP, 2009) and Luebke et al. (ACP, 2013), which are all based on much smaller datasets. Further, we will show the geographical and altitude distribution of IWC, N_ice, R_ice and RH_ice.

Cloud and boundary layer interactions over the Arctic sea-ice in late summer

NASA Astrophysics Data System (ADS)

Shupe, M. D.; Persson, P. O. G.; Brooks, I. M.; Tjernström, M.; Sedlar, J.; Mauritsen, T.; Sjogren, S.; Leck, C.

2013-05-01

Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud-atmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back trajectory analyses suggest that these warm airmasses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these airmasses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixed-layer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

Cloud and boundary layer interactions over the Arctic sea ice in late summer

NASA Astrophysics Data System (ADS)

Shupe, M. D.; Persson, P. O. G.; Brooks, I. M.; Tjernström, M.; Sedlar, J.; Mauritsen, T.; Sjogren, S.; Leck, C.

2013-09-01

Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud-atmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back-trajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixed-layer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David (Technical Monitor)

2002-01-01

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). The 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 (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

Geometric Data Perturbation-Based Personal Health Record Transactions in Cloud Computing

PubMed Central

Balasubramaniam, S.; Kavitha, V.

2015-01-01

Cloud computing is a new delivery model for information technology services and it typically involves the provision of dynamically scalable and often virtualized resources over the Internet. However, cloud computing raises concerns on how cloud service providers, user organizations, and governments should handle such information and interactions. Personal health records represent an emerging patient-centric model for health information exchange, and they are outsourced for storage by third parties, such as cloud providers. With these records, it is necessary for each patient to encrypt their own personal health data before uploading them to cloud servers. Current techniques for encryption primarily rely on conventional cryptographic approaches. However, key management issues remain largely unsolved with these cryptographic-based encryption techniques. We propose that personal health record transactions be managed using geometric data perturbation in cloud computing. In our proposed scheme, the personal health record database is perturbed using geometric data perturbation and outsourced to the Amazon EC2 cloud. PMID:25767826

Geometric data perturbation-based personal health record transactions in cloud computing.

PubMed

Balasubramaniam, S; Kavitha, V

2015-01-01

Cloud computing is a new delivery model for information technology services and it typically involves the provision of dynamically scalable and often virtualized resources over the Internet. However, cloud computing raises concerns on how cloud service providers, user organizations, and governments should handle such information and interactions. Personal health records represent an emerging patient-centric model for health information exchange, and they are outsourced for storage by third parties, such as cloud providers. With these records, it is necessary for each patient to encrypt their own personal health data before uploading them to cloud servers. Current techniques for encryption primarily rely on conventional cryptographic approaches. However, key management issues remain largely unsolved with these cryptographic-based encryption techniques. We propose that personal health record transactions be managed using geometric data perturbation in cloud computing. In our proposed scheme, the personal health record database is perturbed using geometric data perturbation and outsourced to the Amazon EC2 cloud.

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

PubMed

Hu, Jia; Riveros-Iregui, Diego A

2016-04-01

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

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

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

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

Microphysical Cloud Regimes used as a tool to study Aerosol-Cloud-Precipitation-Radiation interactions

NASA Astrophysics Data System (ADS)

Cho, N.; Oreopoulos, L.; Lee, D.

2017-12-01

The presentation will examine whether the diagnostic relationships between aerosol and cloud-affected quantities (precipitation, radiation) obtained from sparse temporal resolution measurements from polar orbiting satellites can potentially demonstrate actual aerosol effects on clouds with appropriate analysis. The analysis relies exclusively on Level-3 (gridded) data and comprises systematic cloud classification in terms of "microphysical cloud regimes" (µCRs), aerosol optical depth (AOD) variations relative to a region's local seasonal climatology, and exploitation of the 3-hour difference between Terra (morning) and Aqua (afternoon) overpasses. Specifically, our presentation will assess whether Aerosol-Cloud-Precipitation-Radiation interactions (ACPRI) can be diagnosed by investigating: (a) The variations with AOD of afternoon cloud-affected quantities composited by afternoon or morning µCRs; (b) µCR transition diagrams composited by morning AOD quartiles; (c) whether clouds represented by ensemble cloud effective radius - cloud optical thickness joint histograms look distinct under low and high AOD conditions when preceded or followed by specific µCRs. We will explain how our approach addresses long-standing themes of the ACPRI problem such as the optimal ways to decompose the problem by cloud class, the prevalence and detectability of 1st/2nd aerosol indirect effects and invigoration, and the effectiveness of aerosol changes in inducing cloud modification at different segments of the AOD distribution.

Measurements of cloud condensation nuclei spectra within maritime cumulus cloud droplets: Implications for mixing processes

NASA Technical Reports Server (NTRS)

Twohy, Cynthia H.; Hudson, James G.

1995-01-01

In a cloud formed during adiabatic expansion, the droplet size distribution will be systematically related to the critical supersaturation of the cloud condensation nuclei (CNN), but this relationship can be complicated in entraining clouds. Useful information about cloud processes, such as mixing, can be obtained from direct measurements of the CNN involved in droplet nucleation. This was accomplished by interfacing two instruments for a series of flights in maritime cumulus clouds. One instrument, the counterflow virtual impactor, collected cloud droplets, and the nonvolatile residual nuclei of the droplets was then passed to a CCN spectrometer, which measured the critical supersaturation (S(sub c)) spectrum of the droplet nuclei. The measured S(sub c) spectra of the droplet nuclei were compared with the S(sub c) spectra of ambient aerosol particles in order to identify which CCN were actually incorporated into droplets and to determine when mixing processes were active at different cloud levels. The droplet nuclei nearly always exhibited lower median S(sub c)'s than the ambient aerosol, as expected since droplets nucleate perferentially on particles with lower critical supersaturations. Critical supersaturation spectra from nuclei of droplets near cloud base were similar to those predicted for cloud regions formed adiabatically, but spectra of droplet nuclei from middle cloud levels showed some evidence that mixing had occurred. Near cloud top, the greatest variation in the spectra of the droplet nuclei was observed, and nuclei with high S(sub c)'s were sometimes present even within relatively large droplets. This suggests that the extent of mixing increases with height in cumulus clouds and that inhomogeneous mixing may be important near cloud top. These promising initial results suggest improvements to the experimental technique that will permit more quantitative results in future experiments.

Geophysical information for teachers: Wave tanks, homemade clouds, glacial goo, and more!

NASA Astrophysics Data System (ADS)

Adamec, Bethany Holm

2012-02-01

AGU is deeply committed to fostering the next generation of Earth and space scientists. Union activities contribute to this effort in many ways, one of which is partnering with the National Earth Science Teacher's Association (NESTA) to hold the Annual Geophysical Information for Teachers (GIFT) workshop at AGU's annual Fall Meeting. GIFT allows K-12 science teachers to hear about the latest geoscience research from the scientists making the discoveries, explore new classroom resources for their students, and visit exhibits and technical sessions of the AGU meeting for free. In 2011 AGU worked with NESTA to develop an improved rigorous and open application process for scientists and education professionals who wished to work as a team and present their Earth and space science work to teachers, as well as lead the educators in a hands-on, classroom- ready activity. Twenty-four applications were received for five slots, so the selected presentations (on tsunamis, clouds, field campaigns, glaciers, and volcanoes), chosen through a peer- review process, truly represented the best ways of getting cutting-edge science into the classroom.

Ionisation in ultra-cool, cloud forming extrasolar planetary atmospheres

NASA Astrophysics Data System (ADS)

Helling, Christiane; the LEAP Team

2015-04-01

Transit spectroscopy provides evidence that extrasolare planets are covered in clouds, a finding that has been forecast by cloud model simulations 15 years ago. Atmospheres are strongly affected by clouds through their large opacity and their chemical activity. Cloud formation models allow to predict cloud particle sizes, their chemical composition and the composition of the remaining atmospheric gas (Woitke & Helling 2004, A&A 414; Helling & Woitke 2006, A&A 455), for example, as input for radiative transfer codes like Drift-Phoenix (Witte et al. 2009; A&A 506). These cloud particles are charged and can discharge, for example in form of lighting (Helling et al. 2013, ApJ 767; Bailey et al. 2014, ApJ 784). Earth observations demonstrate that lighting effects not only the local chemistry but also the electron budget of the atmosphere. This talk will present our work on cloud formation modelling and ionisation processes in cloud forming atmospheres. An hierarchy of ionisation processes leads to a vertically inhomogenously ionised atmosphere which has implications for planetary mass loss and global circulation pattern of planetary atmospheres. Processes involved, like Cosmic Ray ionisation, do also activate the local chemistry such that large hydrocarbon molecules form (Rimmer et al. 2014, IJAsB 13).

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

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 tropics, 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 models simulate cloud 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 cloud systems, The major objective of this paper is to investigate the latent heating, moisture and momenti,im 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 (CCE) model which includes a 3-class ice-phase microphysical scheme, The model domain contains 256 x 256 grid points (using 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km depth) in the vertical, The 2D domain has 1024 grid points. The simulations are performed over a 7 day time period. We will examine (1) the precipitation processes (i.e., condensation/evaporation) and their interaction with warm pool; (2) the heating and moisture budgets in the convective and 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.

Aerosol processing in mixed-phase clouds in ECHAM5-HAM: Model description and comparison to observations

NASA Astrophysics Data System (ADS)

Hoose, C.; Lohmann, U.; Stier, P.; Verheggen, B.; Weingartner, E.

2008-04-01

The global aerosol-climate model ECHAM5-HAM has been extended by an explicit treatment of cloud-borne particles. Two additional modes for in-droplet and in-crystal particles are introduced, which are coupled to the number of cloud droplet and ice crystal concentrations simulated by the ECHAM5 double-moment cloud microphysics scheme. Transfer, production, and removal of cloud-borne aerosol number and mass by cloud droplet activation, collision scavenging, aqueous-phase sulfate production, freezing, melting, evaporation, sublimation, and precipitation formation are taken into account. The model performance is demonstrated and validated with observations of the evolution of total and interstitial aerosol concentrations and size distributions during three different mixed-phase cloud events at the alpine high-altitude research station Jungfraujoch (Switzerland). Although the single-column simulations cannot be compared one-to-one with the observations, the governing processes in the evolution of the cloud and aerosol parameters are captured qualitatively well. High scavenged fractions are found during the presence of liquid water, while the release of particles during the Bergeron-Findeisen process results in low scavenged fractions after cloud glaciation. The observed coexistence of liquid and ice, which might be related to cloud heterogeneity at subgrid scales, can only be simulated in the model when assuming nonequilibrium conditions.

Drizzle formation in stratocumulus clouds: Effects of turbulent mixing

DOE PAGES

Magaritz-Ronen, L.; Pinsky, M.; Khain, A.

2016-02-17

The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian–Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic andmore » characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. Lastly, it was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.« less

Drizzle formation in stratocumulus clouds: Effects of turbulent mixing

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

Magaritz-Ronen, L.; Pinsky, M.; Khain, A.

The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian–Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic andmore » characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. Lastly, it was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.« less

Precipitation microphysics characteristics of a Typhoon Matmo (2014) rainband after landfall over eastern China based on polarimetric radar observations

NASA Astrophysics Data System (ADS)

Wang, Mingjun; Zhao, Kun; Xue, Ming; Zhang, Guifu; Liu, Su; Wen, Long; Chen, Gang

2016-10-01

The evolution of microphysical characteristics of a rainband in Typhoon Matmo (2014) over eastern China, through its onset, developing, mature, and dissipating stages, is documented using observations from an S band polarimetric Doppler radar and a two-dimensional video disdrometer (2DVD). The drop size distributions observed by the 2DVD and retrieved from the polarimetric radar measurements indicate that the convection in the rainband generally contains smaller drops and higher number concentrations than the typical maritime type convection described in Bringi et al. (2003). The average mass-weighted mean diameter (Dm) of convective precipitation in the rainband is about 1.41 mm, and the average logarithmic normalized intercept (Nw) is 4.67 log10 mm-1 m-3. To further investigate the dominant microphysical processes, the evolution of the vertical structures of polarimetric variables is examined. Results show that complex ice processes are involved above the freezing level, while it is most likely that the accretion and/or coalescence processes dominate below the freezing level throughout the rainband life cycle. A combined examination of the polarimetric measurements and profiles of estimated vertical liquid and ice water contents indicates that the conversion of cloud water into rainwater through cloud water accretion by raindrops plays a dominant role in producing heavy rainfall. The high estimated precipitation efficiency of 50% also suggests that cloud water accretion is the dominant mechanism for producing heavy rainfall. This study represents the first time that radar and 2DVD observations are used together to characterize the microphysical characteristics and precipitation efficiency for typhoon rainbands in China.

Services for domain specific developments in the Cloud

NASA Astrophysics Data System (ADS)

Schwichtenberg, Horst; Gemuend, André

2015-04-01

We will discuss and demonstrate the possibilities of new Cloud Services where the complete development of code is in the Cloud. We will discuss the possibilities of such services where the complete development cycle from programing to testing is in the cloud. This can be also combined with dedicated research domain specific services and hide the burden of accessing available infrastructures. As an example, we will show a service that is intended to complement the services of the VERCE projects infrastructure, a service that utilizes Cloud resources to offer simplified execution of data pre- and post-processing scripts. It offers users access to the ObsPy seismological toolbox for processing data with the Python programming language, executed on virtual Cloud resources in a secured sandbox. The solution encompasses a frontend with a modern graphical user interface, a messaging infrastructure as well as Python worker nodes for background processing. All components are deployable in the Cloud and have been tested on different environments based on OpenStack and OpenNebula. Deployments on commercial, public Clouds will be tested in the future.

Heat and moisture fluxes within a nighttime maritime stratus cloud during CASP II

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

Gultepe, I.; Issac, G.

Stratus clouds in the lower part of the atmosphere over the ocean or land can play an important role in boundary layer processes and in climate change. Physical, dynamical, and radiative processes within marine stratus clouds on both cloud and regional scale are studied for the first time during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) (Albrecht et al., 1988). These clouds can effect the nowcasting, pollution transfer, and radiative processes (Nicholls and Leighton, 1986). Similar to the FIRE stratus project, the Canadian Atlantic Storms Program (CASP) II field project was planned to obtain a bettermore » understanding of cloud physical, dynamical, radiative characteristics, and mesoscale structure of Canadian east coast storms. Here the dynamical and microphysical data, and a radiative transfer model are used to better understand a developing nighttime stratus cloud over the ocean during CASP II which took place over Atlantic Canada. Observations collected by the Convair aircraft of the National Research Council (NRC) of Canada during the CASP II field project on February 6, 1991 are presented.« less

Understanding Rapid Changes in Phase Partitioning between Cloud Liquid and Ice in Stratiform Mixed-Phase Clouds: An Arctic Case Study

DOE PAGES

Kalesse, Heike; de Boer, Gijs; Solomon, Amy; ...

2016-11-23

Understanding phase transitions in mixed-phase clouds is of great importance because the hydrometeor phase controls the lifetime and radiative effects of clouds. These cloud radiative effects have a crucial impact on the surface energy budget and thus on the evolution of the ice cover, in high altitudes. For a springtime low-level mixed-phase stratiform cloud case from Barrow, Alaska, a unique combination of instruments and retrieval methods is combined with multiple modeling perspectives to determine key processes that control cloud phase partitioning. The interplay of local cloud-scale versus large-scale processes is considered. Rapid changes in phase partitioning were found to bemore » caused by several main factors. Some major influences were the large-scale advection of different air masses with different aerosol concentrations and humidity content, cloud-scale processes such as a change in the thermodynamical coupling state, and local-scale dynamics influencing the residence time of ice particles. Other factors such as radiative shielding by a cirrus and the influence of the solar cycle were found to only play a minor role for the specific case study (11–12 March 2013). Furthermore, for an even better understanding of cloud phase transitions, observations of key aerosol parameters such as profiles of cloud condensation nucleus and ice nucleus concentration are desirable.« less

Understanding Rapid Changes in Phase Partitioning between Cloud Liquid and Ice in Stratiform Mixed-Phase Clouds: An Arctic Case Study

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

Kalesse, Heike; de Boer, Gijs; Solomon, Amy

Understanding phase transitions in mixed-phase clouds is of great importance because the hydrometeor phase controls the lifetime and radiative effects of clouds. These cloud radiative effects have a crucial impact on the surface energy budget and thus on the evolution of the ice cover, in high altitudes. For a springtime low-level mixed-phase stratiform cloud case from Barrow, Alaska, a unique combination of instruments and retrieval methods is combined with multiple modeling perspectives to determine key processes that control cloud phase partitioning. The interplay of local cloud-scale versus large-scale processes is considered. Rapid changes in phase partitioning were found to bemore » caused by several main factors. Some major influences were the large-scale advection of different air masses with different aerosol concentrations and humidity content, cloud-scale processes such as a change in the thermodynamical coupling state, and local-scale dynamics influencing the residence time of ice particles. Other factors such as radiative shielding by a cirrus and the influence of the solar cycle were found to only play a minor role for the specific case study (11–12 March 2013). Furthermore, for an even better understanding of cloud phase transitions, observations of key aerosol parameters such as profiles of cloud condensation nucleus and ice nucleus concentration are desirable.« less

2D Radiative Processes Near Cloud Edges

NASA Technical Reports Server (NTRS)

Varnai, T.

2012-01-01

Because of the importance and complexity of dynamical, microphysical, and radiative processes taking place near cloud edges, the transition zone between clouds and cloud free air has been the subject of intense research both in the ASR program and in the wider community. One challenge in this research is that the one-dimensional (1D) radiative models widely used in both remote sensing and dynamical simulations become less accurate near cloud edges: The large horizontal gradients in particle concentrations imply that accurate radiative calculations need to consider multi-dimensional radiative interactions among areas that have widely different optical properties. This study examines the way the importance of multidimensional shortwave radiative interactions changes as we approach cloud edges. For this, the study relies on radiative simulations performed for a multiyear dataset of clouds observed over the NSA, SGP, and TWP sites. This dataset is based on Microbase cloud profiles as well as wind measurements and ARM cloud classification products. The study analyzes the way the difference between 1D and 2D simulation results increases near cloud edges. It considers both monochromatic radiances and broadband radiative heating, and it also examines the influence of factors such as cloud type and height, and solar elevation. The results provide insights into the workings of radiative processes and may help better interpret radiance measurements and better estimate the radiative impacts of this critical region.

GEWEX Continental-scale International Project (GCIP)

NASA Technical Reports Server (NTRS)

Try, Paul

1993-01-01

The Global Energy and Water Cycle Experiment (GEWEX) represents the World Climate Research Program activities on clouds, radiation, and land-surface processes. The goal of the program is to reproduce and predict, by means of suitable models, the variations of the global hydrological regime and its impact on atmospheric and oceanic dynamics. However, GEWEX is also concerned with variations in regional hydrological processes and water resources and their response to changes in the environment such as increasing greenhouse gases. In fact, GEWEX contains a major new international project called the GEWEX Continental-scale International Project (GCIP), which is designed to bridge the gap between the small scales represented by hydrological models and those scales that are practical for predicting the regional impacts of climate change. The development and use of coupled mesoscale-hydrological models for this purpose is a high priority in GCIP. The objectives of GCIP are presented.

Proceedings of a Workshop on Polar Stratospheric Clouds: Their Role in Atmospheric Processes

NASA Technical Reports Server (NTRS)

Hamill, P. (Editor); Mcmaster, L. R. (Editor)

1984-01-01

The potential role of polar stratospheric clouds in atmospheric processes was assessed. The observations of polar stratospheric clouds with the Nimbus 7 SAM II satellite experiment were reviewed and a preliminary analysis of their formation, impact on other remote sensing experiments, and potential impact on climate were presented. The potential effect of polar stratospheric clouds on climate, radiation balance, atmospheric dynamics, stratospheric chemistry and water vapor budget, and cloud microphysics was assessed. Conclusions and recommendations, a synopsis of materials and complementary material to support those conclusions and recommendations are presented.

Organic condensation: A vital link connecting aerosol formation to climate forcing (Invited)

NASA Astrophysics Data System (ADS)

Riipinen, I.; Pierce, J. R.; Yli-Juuti, T.; Nieminen, T.; Häkkinen, S.; Ehn, M.; Junninen, H.; Lehtipalo, K.; Petdjd, T. T.; Slowik, J. G.; Chang, R. Y.; Shantz, N. C.; Abbatt, J.; Leaitch, W. R.; Kerminen, V.; Worsnop, D. R.; Pandis, S. N.; Donahue, N. M.; Kulmala, M. T.

2010-12-01

Aerosol-cloud interactions represent the largest uncertainty in calculations of Earth’s radiative forcing. Number concentrations of atmospheric aerosol particles are in the core of this uncertainty, as they govern the numbers of cloud condensation nuclei (CCN) and influence the albedo and lifetime of clouds. Aerosols also impair air quality through their adverse effects on atmospheric visibility and human health. The ultrafine fraction (<100 nm) of atmospheric aerosol particles often dominates the total aerosol numbers, and nucleation of atmospheric vapours is one of the most important sources of these particles. To have climatic relevance, however, the freshly-nucleated particles need to grow in size, and consequently their climatic importance remains to be quantified (see Fig. 1). We combine observations from two continental sites (Egbert, Canada and Hyytiälä, Finland) to show that condensation of organic vapours is a crucial factor governing the lifetimes and climatic importance of the smallest atmospheric particles. We demonstrate that state-of-the-science organic gas-particle partitioning models fail to reproduce the observations; we propose a new modelling approach that is consistent with the measurements. Finally, we demonstrate the large sensitivity of climatic forcing of atmospheric aerosols to these interactions between organic vapours and the smallest atmospheric nanoparticles - highlighting the need for representing this process in global climate models. Figure 1. Organic emissions and the dynamic processes governing the climatic importance of ultrafine aerosol. Condensable vapours are produced upon oxidation of volatile organic compounds (VOCs) and can 1) nucleate to form new small particles; 2) grow freshly formed particles to larger sizes and increase their probability to serve as CCN; 3) condense on the background aerosol (> 100 nm) and enhance the loss of ultrafine particles. Primary organic aerosol (POA) contributes to the large end of the aerosol size distribution, enhancing the scavenging of the ultrafine particles.

Laser vaporization of cirrus-like ice particles with secondary ice multiplication

PubMed Central

Matthews, Mary; Pomel, François; Wender, Christiane; Kiselev, Alexei; Duft, Denis; Kasparian, Jérôme; Wolf, Jean-Pierre; Leisner, Thomas

2016-01-01

We investigate the interaction of ultrashort laser filaments with individual 90-μm ice particles, representative of cirrus particles. The ice particles fragment under laser illumination. By monitoring the evolution of the corresponding ice/vapor system at up to 140,000 frames per second over 30 ms, we conclude that a shockwave vaporization supersaturates the neighboring region relative to ice, allowing the nucleation and growth of new ice particles, supported by laser-induced plasma photochemistry. This process constitutes the first direct observation of filament-induced secondary ice multiplication, a process that strongly modifies the particle size distribution and, thus, the albedo of typical cirrus clouds. PMID:27386537

Laser vaporization of cirrus-like ice particles with secondary ice multiplication.

PubMed

Matthews, Mary; Pomel, François; Wender, Christiane; Kiselev, Alexei; Duft, Denis; Kasparian, Jérôme; Wolf, Jean-Pierre; Leisner, Thomas

2016-05-01

We investigate the interaction of ultrashort laser filaments with individual 90-μm ice particles, representative of cirrus particles. The ice particles fragment under laser illumination. By monitoring the evolution of the corresponding ice/vapor system at up to 140,000 frames per second over 30 ms, we conclude that a shockwave vaporization supersaturates the neighboring region relative to ice, allowing the nucleation and growth of new ice particles, supported by laser-induced plasma photochemistry. This process constitutes the first direct observation of filament-induced secondary ice multiplication, a process that strongly modifies the particle size distribution and, thus, the albedo of typical cirrus clouds.

Stratus Cloud Radiative Effects from Cloud Processed Bimodal CCN Distributions

NASA Astrophysics Data System (ADS)

Noble, S. R., Jr.; Hudson, J. G.

2016-12-01

Inability to understand cloud processes is a large component of climate uncertainty. Increases in cloud condensation nuclei (CCN) concentrations are known to increase cloud droplet number concentrations (Nc). This aerosol-cloud interaction (ACI) produces greater Nc at smaller sizes, which brightens clouds. A lesser understood ACI is cloud processing of CCN. This improves CCN that then more easily activate at lower cloud supersaturations (S). Bimodal CCN distributions thus ensue from these evaporated cloud droplets. Hudson et al. (2015) related CCN bimodality to Nc. In stratus clouds, bimodal CCN created greater Nc whereas in cumulus less Nc. Thus, CCN distribution shape influences cloud properties; microphysics and radiative properties. Measured uni- and bimodal CCN distributions were input into an adiabatic droplet growth model using various specified vertical wind speeds (W). Bimodal CCN produced greater Nc (Fig. 1a) and smaller mean diameters (MD; Fig. 1b) at lower W typical of stratus clouds (<70 cm/s). Improved CCN (low critical S) were more easily activated at the lower S of stratus from low W, thus, creating greater Nc. Competition for condensate thus reduced MD and drizzle. At greater W, typical of cumulus clouds (>70 cm/s), bimodal CCN made lower Nc with larger MD thus enhancing drizzle whereas unimodal CCN made greater Nc with smaller MD, thus reducing drizzle. Thus, theoretical predictions of Nc and MD for uni- and bimodal CCN agree with the sense of the observations. Radiative effects were determined using a cloud grown to a 250-meter thickness. Bimodal CCN at low W reduced cloud effective radius (re), made greater cloud optical thickness (COT), and made greater cloud albedo (Fig. 1c). At very low W changes were as much as +9% for albedo, +17% for COT, and -12% for re. Stratus clouds typically have low W and cover large areas. Thus, these changes in cloud radiative properties at low W impact climate. Stratus cloud susceptibility to CCN distribution thus requires further investigation to determine their impact on ACI. Hudson et al. (2015), JGRA, 120, 3436-3452.

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Adventures in Private Cloud: Balancing Cost and Capability at the CloudSat Data Processing Center

NASA Astrophysics Data System (ADS)

Partain, P.; Finley, S.; Fluke, J.; Haynes, J. M.; Cronk, H. Q.; Miller, S. D.

2016-12-01

Since the beginning of the CloudSat Mission in 2006, The CloudSat Data Processing Center (DPC) at the Cooperative Institute for Research in the Atmosphere (CIRA) has been ingesting data from the satellite and other A-Train sensors, producing data products, and distributing them to researchers around the world. The computing infrastructure was specifically designed to fulfill the requirements as specified at the beginning of what nominally was a two-year mission. The environment consisted of servers dedicated to specific processing tasks in a rigid workflow to generate the required products. To the benefit of science and with credit to the mission engineers, CloudSat has lasted well beyond its planned lifetime and is still collecting data ten years later. Over that period requirements of the data processing system have greatly expanded and opportunities for providing value-added services have presented themselves. But while demands on the system have increased, the initial design allowed for very little expansion in terms of scalability and flexibility. The design did change to include virtual machine processing nodes and distributed workflows but infrastructure management was still a time consuming task when system modification was required to run new tests or implement new processes. To address the scalability, flexibility, and manageability of the system Cloud computing methods and technologies are now being employed. The use of a public cloud like Amazon Elastic Compute Cloud or Google Compute Engine was considered but, among other issues, data transfer and storage cost becomes a problem especially when demand fluctuates as a result of reprocessing and the introduction of new products and services. Instead, the existing system was converted to an on premises private Cloud using the OpenStack computing platform and Ceph software defined storage to reap the benefits of the Cloud computing paradigm. This work details the decisions that were made, the benefits that have been realized, the difficulties that were encountered and issues that still exist.

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

Nicoll, Ken A.; O'Connor, E.

Large-scale properties of clouds such as lifetime, optical thickness, and precipitation are all dependent on small-scale cloud microphysical processes. Such processes determine when droplets will grow or shrink, their size, and the number of cloud droplets. Although our understanding of cloud microphysics has vastly improved over the past several decades with the development of remote sensing methods such as lidar and radar, there remain a number of processes that are not well understood, such as the effect of electrical charge on cloud microphysics. To understand the various processes and feedback mechanisms, high-vertical–resolution observations are required. Radiosondes provide an ideal platformmore » for providing routine vertical profiles of in situ measurements at any location (with a vertical resolution of a few meters). Modified meteorological radiosondes have been extensively developed at the University of Reading for measuring cloud properties, to allow measurements beyond the traditional thermodynamic quantities (pressure, temperature and relative humidity) to be obtained cost-effectively. This project aims to investigate a number of cloud processes in which in situ cloud observations from these modified radiosondes can provide information either complementary to or not obtainable by lidar/radar systems. During two intensive operational periods (IOPs) in May and August 2014 during deployment to Hyytiälä, Finland, the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Second ARM Mobile Facility (AMF2) launched a total of 24 instrumented radiosondes through a number of different cloud types ranging from low-level stratiform cloud to cumulonimbus. Twelve balloon flights of an accelerometer turbulence sensor were made, which detected significant turbulence on eleven of these flights. Most of the turbulent episodes encountered were due to convective processes, but several were associated with the transition from troposphere to stratosphere at the tropopause. Similarities in the location of turbulent layers were generally found between the balloon turbulence sensor and the Ka-band radar, but with discrepancies between the orders of magnitude of turbulence detected. The reason for these discrepancies is the subject of future work.« less

RACORO Continental Boundary Layer Cloud Investigations: 1. Case Study Development and Ensemble Large-Scale Forcings

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang;

RACORO continental boundary layer cloud investigations: 1. Case study development and ensemble large-scale forcings

NASA Astrophysics Data System (ADS)

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang; Li, Zhijin; Xie, Shaocheng; Ackerman, Andrew S.; Zhang, Minghua; Khairoutdinov, Marat

2015-06-01

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

Minimalist model of ice microphysics in mixed-phase stratiform clouds

NASA Astrophysics Data System (ADS)

Yang, F.; Ovchinnikov, M.; Shaw, R. A.

2013-12-01

The question of whether persistent ice crystal precipitation from supercooled layer clouds can be explained by time-dependent, stochastic ice nucleation is explored using an approximate, analytical model and a large-eddy simulation (LES) cloud model. The updraft velocity in the cloud defines an accumulation zone, where small ice particles cannot fall out until they are large enough, which will increase the residence time of ice particles in the cloud. Ice particles reach a quasi-steady state between growth by vapor deposition and fall speed at cloud base. The analytical model predicts that ice water content (wi) has a 2.5 power-law relationship with ice number concentration (ni). wi and ni from a LES cloud model with stochastic ice nucleation confirm the 2.5 power-law relationship, and initial indications of the scaling law are observed in data from the Indirect and Semi-Direct Aerosol Campaign. The prefactor of the power law is proportional to the ice nucleation rate and therefore provides a quantitative link to observations of ice microphysical properties. Ice water content (wi) and ice number concentration (ni) relationship from LES. a and c: Accumulation zone region; b and d: Selective accumulation zone region. Black lines in c and d are best fitted 2.5 slope lines. Colors in Figures a and b represent updraft velocity, while colors in c and d represent altitude. The cloud base and top are at about 600 m and 800 m, respectively. Ice water content (wi) and ice number concentration (ni) relationship for two ice nucleation rates. Blue points are from LES with low ice nucleation rate and red points with high ice nucleation rate. Solid and dashed lines are best fitted 2.5 slope lines.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Improving volcanic sulfur dioxide cloud dispersal forecasts by progressive assimilation of satellite observations

NASA Astrophysics Data System (ADS)

Boichu, Marie; Clarisse, Lieven; Khvorostyanov, Dmitry; Clerbaux, Cathy

2014-04-01

Forecasting the dispersal of volcanic clouds during an eruption is of primary importance, especially for ensuring aviation safety. As volcanic emissions are characterized by rapid variations of emission rate and height, the (generally) high level of uncertainty in the emission parameters represents a critical issue that limits the robustness of volcanic cloud dispersal forecasts. An inverse modeling scheme, combining satellite observations of the volcanic cloud with a regional chemistry-transport model, allows reconstructing this source term at high temporal resolution. We demonstrate here how a progressive assimilation of freshly acquired satellite observations, via such an inverse modeling procedure, allows for delivering robust sulfur dioxide (SO2) cloud dispersal forecasts during the eruption. This approach provides a computationally cheap estimate of the expected location and mass loading of volcanic clouds, including the identification of SO2-rich parts.

Vertical distribution of clouds over Hampton, Virginia observed by lidar under the ECLIPS and FIRE ETO programs

NASA Technical Reports Server (NTRS)

Vaughan, M. A.; Winker, D. M.

1994-01-01

Intensive cloud lidar observations have been made by NASA Langley Research Center during the two observation phases of the ECLIPS project. Less intensive but longer term observations have been conducted as part of the FIRE extended time observation (ETO) program since 1987. We present a preliminary analysis of the vertical distribution of clouds based on these observations. A mean cirrus thickness of just under 1 km has been observed with a mean altitude of about 80 percent of the tropopause height. Based on the lidar data, cirrus coverage was estimated to be just under 20 percent, representing roughly 50 percent of all clouds studied. Cirrus was observed to have less seasonal variation than lower clouds. Mid-level clouds are found to occur primarily in association with frontal activity.

Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

EPA Science Inventory

Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

Fungal spores as potential ice nuclei in fog/cloud water and snow

NASA Astrophysics Data System (ADS)

Bauer, Heidi; Goncalves, Fabio L. T.; Schueller, Elisabeth; Puxbaum, Hans

2010-05-01

INTRODUCTION: In discussions about climate change and precipitation frequency biological ice nucleation has become an issue. While bacterial ice nucleation (IN) is already well characterized and even utilized in industrial processes such as the production of artificial snow or to improve freezing processes in food industry, less is known about the IN potential of fungal spores which are also ubiquitous in the atmosphere. A recent study performed at a mountain top in the Rocky Mountains suggests that fungal spores and/or pollen might play a role in increased IN abundance during periods of cloud cover (Bowers et al. 2009). In the present work concentrations of fungal spores in fog/cloud water and snow were determined. EXPERIMENTAL: Fog samples were taken with an active fog sampler in 2008 in a traffic dominated area and in a national park in São Paulo, Brazil. The number concentrations of fungal spores were determined by microscopic by direct enumeration by epifluorescence microscopy after staining with SYBR Gold nucleic acid gel stain (Bauer et al. 2008). RESULTS: In the fog water collected in the polluted area at a junction of two highly frequented highways around 22,000 fungal spores mL-1 were counted. Fog in the national park contained 35,000 spores mL-1. These results were compared with cloud water and snow samples from Mt. Rax, situated at the eastern rim of the Austrian Alps. Clouds contained on average 5,900 fungal spores mL-1 cloud water (1,300 - 11,000) or 2,200 spores m-3 (304 - 5,000). In freshly fallen snow spore concentrations were lower than in cloud water, around 1,000 fungal spores mL-1 were counted (Bauer et al. 2002). In both sets of samples representatives of the ice nucleating genus Fusarium could be observed. REFERENCES: Bauer, H., Kasper-Giebl, A., Löflund, M., Giebl, H., Hitzenberger, R., Zibuschka, F., Puxbaum, H. (2002). The contribution of bacteria and fungal spores to the organic carbon content of cloud water, precipitation and aerosols. Atmos. Res. 64, 109-119. Bauer, H., Schueller, E., Weinke, G. Berger, A., Hitzenberger, R., Marr, I.L., Puxbaum, H. (2008). Significant contributions of fungal spores to the organic carbon and to the aerosol mass balance of the urban atmospheric aerosol. Atmos. Environ. 42, 5542-5549. Bowers, R.M., Lauber, C.L., Wiedinmyer, C., Hamady, M., Hallar, A.G., Fall, R., Knight, R., Fierer, N. (2009). Characterization of airborne microbial communities at a high-elevation site and their potential to act as atmospheric ice nuclei. Appl. Environ. Microbiol: 75, 5121-5130.

OT1_mputman_1: ASCII: All Sky observations of Galactic CII

NASA Astrophysics Data System (ADS)

Putman, M.

2010-07-01

The Milky Way and other galaxies require a significant source of ongoing star formation fuel to explain their star formation histories. A new ubiquitous population of discrete, cold clouds have recently been discovered at the disk-halo interface of our Galaxy that could potentially provide this source of fuel. We propose to observe a small sample of these disk-halo clouds with HIFI to determine if the level of [CII] emission detected suggests they represent the cooling of warm clouds at the interface between the star forming disk and halo. These cooling clouds are predicted by simulations of warm clouds moving into the disk-halo interface region. We target 5 clouds in this proposal for which we have high resolution HI maps and can observe the densest core of the cloud. The results of our observations will also be used to interpret the surprisingly high detections of [CII] for low HI column density clouds in the Galactic Plane by the GOT C+ Key Program by extending the clouds probed to high latitude environments.

Multi-wavelength dual polarisation lidar for monitoring precipitation process in the cloud seeding technique

NASA Astrophysics Data System (ADS)

Sudhakar, P.; Sheela, K. Anitha; Ramakrishna Rao, D.; Malladi, Satyanarayana

2016-05-01

In recent years weather modification activities are being pursued in many countries through cloud seeding techniques to facilitate the increased and timely precipitation from the clouds. In order to induce and accelerate the precipitation process clouds are artificially seeded with suitable materials like silver iodide, sodium chloride or other hygroscopic materials. The success of cloud seeding can be predicted with confidence if the precipitation process involving aerosol, the ice water balance, water vapor content and size of the seeding material in relation to aerosol in the cloud is monitored in real time and optimized. A project on the enhancement of rain fall through cloud seeding is being implemented jointly with Kerala State Electricity Board Ltd. Trivandrum, Kerala, India at the catchment areas of the reservoir of one of the Hydro electric projects. The dual polarization lidar is being used to monitor and measure the microphysical properties, the extinction coefficient, size distribution and related parameters of the clouds. The lidar makes use of the Mie, Rayleigh and Raman scattering techniques for the various measurement proposed. The measurements with the dual polarization lidar as above are being carried out in real time to obtain the various parameters during cloud seeding operations. In this paper we present the details of the multi-wavelength dual polarization lidar being used and the methodology to monitor the various cloud parameters involved in the precipitation process. The necessary retrieval algorithms for deriving the microphysical properties of clouds, aerosols characteristics and water vapor profiles are incorporated as a software package working under Lab-view for online and off line analysis. Details on the simulation studies and the theoretical model developed in this regard for the optimization of various parameters are discussed.

Hands-on, online, and workshop-based K-12 weather and climate education resources from the Center for Multi-scale Modeling of Atmospheric Processes

NASA Astrophysics Data System (ADS)

Foster, S. Q.; Johnson, R. M.; Randall, D. A.; Denning, A.; Burt, M. A.; Gardiner, L.; Genyuk, J.; Hatheway, B.; Jones, B.; La Grave, M. L.; Russell, R. M.

2009-12-01

The need for improving the representation of cloud processes in climate models has been one of the most important limitations of the reliability of climate-change simulations. Now in its fourth year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University (CSU) is addressing this problem through a revolutionary new approach to representing cloud processes on their native scales, including the cloud-scale interaction processes that are active in cloud systems. CMMAP has set ambitious education and human-resource goals to share basic information about the atmosphere, clouds, weather, climate, and modeling with diverse K-12 and public audiences. This is accomplished through collaborations in resource development and dissemination between CMMAP scientists, CSU’s Little Shop of Physics (LSOP) program, and the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). Little Shop of Physics develops new hands on science activities demonstrating basic science concepts fundamental to understanding atmospheric characteristics, weather, and climate. Videos capture demonstrations of children completing these activities which are broadcast to school districts and public television programs. CMMAP and LSOP educators and scientists partner in teaching a summer professional development workshops for teachers at CSU with a semester's worth of college-level content on the basic physics of the atmosphere, weather, climate, climate modeling, and climate change, as well as dozens of LSOP inquiry-based activities suitable for use in classrooms. The W2U project complements these efforts by developing and broadly disseminating new CMMAP-related online content pages, animations, interactives, image galleries, scientists’ biographies, and LSOP videos to K-12 and public audiences. Reaching nearly 20 million users annually, W2U is highly valued as a curriculum enhancement resource, because its content is written at three levels in English and Spanish. Links between science topics and literature, art, and mythology enable teachers of English Language Learners, literacy, and the arts to integrate science into their classrooms. In summary, the CMMAP NSF-funded Science and Technology Center has established a highly effective and productive partnership of scientists and educators focused on enhancing public science literacy about weather, climate, and global change. All CMMAP, LSOP, and W2U resources can be accessed online at no cost by the entire atmospheric science K-12 and informal science education community.

Changes in cloud properties over East Asia deduced from the CLARA-A2 satellite data record

NASA Astrophysics Data System (ADS)

Benas, Nikos; Fokke Meirink, Jan; Hollmann, Rainer; Karlsson, Karl-Göran; Stengel, Martin

2017-04-01

Studies on cloud properties and processes, and their role in the Earth's changing climate, have advanced during the past decades. A significant part of this advance was enabled by satellite measurements, which offer global and continuous monitoring. Lately, a new satellite-based cloud data record was released: the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - second edition (CLARA-A2) includes high resolution cloud macro- and micro-physical properties derived from the AVHRR instruments on board NOAA and MetOp polar orbiters. Based on this data record, an analysis of cloud property changes over East Asia during the 12-year period 2004-2015 was performed. Significant changes were found in both optical and geometric cloud properties, including increases in cloud liquid water path and top height. The Cloud Droplet Number Concentration (CDNC) was specifically studied in order to gain further insight into possible connections between aerosol and cloud processes. To this end, aerosol and cloud observations from MODIS, covering the same area and period, were included in the analysis.

Cloud Chemistry in the United States: Problems and Prospects

NASA Astrophysics Data System (ADS)

Carlton, A. G.; Barth, M. C.; Lance, S.; Fahey, K.; McNeill, V. F.; Weber, R. J.

2017-12-01

Clouds cover 60% of the Earth's surface at a given time and are the primary means by which atmospheric trace species are lofted from the polluted boundary layer to the free troposphere. Clouds also play an important role as atmospheric aqueous phase reactors, scavenging soluble gas phase precursors and providing a medium for oxidation reactions that yield lower volatility products that contribute to increased aerosol mass when cloud drops evaporate. On a global average, most sulfate particles are formed during cloud processing, and organic particles known to form through aqueous phase pathways are found above clouds. However, atmospheric chemistry observations are generally biased for clear sky conditions. For example, aircraft field deployments typically avoid clouds. Satellite retrievals impacted by clouds are often screened from the final data products. This hinders knowledge of cloud chemistry and the impacts on tropospheric composition. In this work, we explore temporal and geospatial trends in trace species related to cloud processing in the U.S. with a focus on organic chemistry. We apply 3-dimensional and 0-dimensional models to recent campaigns and mountaintop cloud sampling sites, and compare to measurements.

The Nature of Carbon Dioxide Bearing Ices in Quiescent Molecular Clouds

NASA Astrophysics Data System (ADS)

Whittet, D. C. B.; Cook, A. M.; Chiar, J. E.; Pendleton, Y. J.; Shenoy, S. S.; Gerakines, P. A.

2009-04-01

The properties of the ices that form in dense molecular clouds represent an important set of initial conditions in the evolution of interstellar and preplanetary matter in regions of active star formation. Of the various spectral features available for study, the bending mode of solid CO2 near 15 μm has proven to be a particularly sensitive probe of physical conditions, especially temperature. We present new observations of this absorption feature in the spectrum of Q21-1, a background field star located behind a dark filament in the Cocoon Nebula (IC 5146). We show the profile of the feature to be consistent with a two-component (polar + nonpolar) model for the ices, based on spectra of laboratory analogs with temperatures in the range 10-20 K. The polar component accounts for ~85% of the CO2 in the line of sight. We compare for the first time 15 μm profiles in three widely separated dark clouds (Taurus, Serpens, and IC 5146), and show that they are indistinguishable to within observational scatter. Systematic differences in the observed CO2/H2O ratio in the three clouds have little or no effect on the 15 μm profile. The abundance of elemental oxygen in the ices appears to be a unifying factor, displaying consistent behavior in the three clouds. We conclude that the ice formation process is robust and uniformly efficient, notwithstanding compositional variations arising from differences in how the O is distributed between the primary species (H2O, CO2, and CO) in the ices.

A Big Data Approach for Situation-Aware estimation, correction and prediction of aerosol effects, based on MODIS Joint Atmosphere product (collection 6) time series data

NASA Astrophysics Data System (ADS)

Singh, A. K.; Toshniwal, D.

2017-12-01

The MODIS Joint Atmosphere product, MODATML2 and MYDATML2 L2/3 provided by LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center) re-sampled from medium resolution MODIS Terra /Aqua Satellites data at 5km scale, contains Cloud Reflectance, Cloud Top Temperature, Water Vapor, Aerosol Optical Depth/Thickness, Humidity data. These re-sampled data, when used for deriving climatic effects of aerosols (particularly in case of cooling effect) still exposes limitations in presence of uncertainty measures in atmospheric artifacts such as aerosol, cloud, cirrus cloud etc. The effect of uncertainty measures in these artifacts imposes an important challenge for estimation of aerosol effects, adequately affecting precise regional weather modeling and predictions: Forecasting and recommendation applications developed largely depend on these short-term local conditions (e.g. City/Locality based recommendations to citizens/farmers based on local weather models). Our approach inculcates artificial intelligence technique for representing heterogeneous data(satellite data along with air quality data from local weather stations (i.e. in situ data)) to learn, correct and predict aerosol effects in the presence of cloud and other atmospheric artifacts, defusing Spatio-temporal correlations and regressions. The Big Data process pipeline consisting correlation and regression techniques developed on Apache Spark platform can easily scale for large data sets including many tiles (scenes) and over widened time-scale. Keywords: Climatic Effects of Aerosols, Situation-Aware, Big Data, Apache Spark, MODIS Terra /Aqua, Time Series

Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images

NASA Astrophysics Data System (ADS)

Xie, L.; Hu, H.; Zhu, Q.; Wu, B.; Zhang, Y.

2017-05-01

Despite the success of multi-view stereo (MVS) reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

Screening of cloud microorganisms isolated at the Puy de Dôme (France) station for the production of biosurfactants

NASA Astrophysics Data System (ADS)

Renard, Pascal; Canet, Isabelle; Sancelme, Martine; Wirgot, Nolwenn; Deguillaume, Laurent; Delort, Anne-Marie

2016-09-01

A total of 480 microorganisms collected from 39 clouds sampled at the Puy de Dôme station (alt. 1465 m; 45°46'19'' N, 2°57'52'' E; Massif Central, France) were isolated and identified. This unique collection was screened for biosurfactant (surfactants of microbial origin) production by measuring the surface tension (σ) of the crude extracts, comprising the supernatants of the pure cultures, using the pendant drop technique. The results showed that 41 % of the tested strains were active producers (σ < 55 mN m-1), with 7 % being extremely active (σ < 30 mN m-1). The most efficient biosurfactant producers (σ < 45 mN m-1) belong to a few bacterial genera (Pseudomonas and Xanthomonas) from the Υ-Proteobacteria class (78 %) and a yeast genus (Udeniomyces) from the Basidiomycota phylum (11 %). Some Bacillus strains from the Firmicutes phylum were also active but represented a small fraction of the collected population. Strains from the Actinobacteria phylum in the collection examined in the present study showed moderate biosurfactant production (45<σ < 55 mN m-1). Pseudomonas (Υ-Proteobacteria), the most frequently detected genus in clouds, with some species issued from the phyllosphere, was the dominant group for the production of biosurfactants. We observed some correlations between the chemical composition of cloud water and the presence of biosurfactant-producing microorganisms, suggesting the "biogeography" of this production. Moreover, the potential impact of the production of biosurfactants by cloud microorganisms on atmospheric processes is discussed.

Space Situational Awareness Data Processing Scalability Utilizing Google Cloud Services

NASA Astrophysics Data System (ADS)

Greenly, D.; Duncan, M.; Wysack, J.; Flores, F.

Space Situational Awareness (SSA) is a fundamental and critical component of current space operations. The term SSA encompasses the awareness, understanding and predictability of all objects in space. As the population of orbital space objects and debris increases, the number of collision avoidance maneuvers grows and prompts the need for accurate and timely process measures. The SSA mission continually evolves to near real-time assessment and analysis demanding the need for higher processing capabilities. By conventional methods, meeting these demands requires the integration of new hardware to keep pace with the growing complexity of maneuver planning algorithms. SpaceNav has implemented a highly scalable architecture that will track satellites and debris by utilizing powerful virtual machines on the Google Cloud Platform. SpaceNav algorithms for processing CDMs outpace conventional means. A robust processing environment for tracking data, collision avoidance maneuvers and various other aspects of SSA can be created and deleted on demand. Migrating SpaceNav tools and algorithms into the Google Cloud Platform will be discussed and the trials and tribulations involved. Information will be shared on how and why certain cloud products were used as well as integration techniques that were implemented. Key items to be presented are: 1.Scientific algorithms and SpaceNav tools integrated into a scalable architecture a) Maneuver Planning b) Parallel Processing c) Monte Carlo Simulations d) Optimization Algorithms e) SW Application Development/Integration into the Google Cloud Platform 2. Compute Engine Processing a) Application Engine Automated Processing b) Performance testing and Performance Scalability c) Cloud MySQL databases and Database Scalability d) Cloud Data Storage e) Redundancy and Availability

Implementation of aerosol-cloud interactions in the regional atmosphere-aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

NASA Astrophysics Data System (ADS)

Dipu, Sudhakar; Quaas, Johannes; Wolke, Ralf; Stoll, Jens; Mühlbauer, Andreas; Sourdeval, Odran; Salzmann, Marc; Heinold, Bernd; Tegen, Ina

2017-06-01

The regional atmospheric model Consortium for Small-scale Modeling (COSMO) coupled to the Multi-Scale Chemistry Aerosol Transport model (MUSCAT) is extended in this work to represent aerosol-cloud interactions. Previously, only one-way interactions (scavenging of aerosol and in-cloud chemistry) and aerosol-radiation interactions were included in this model. The new version allows for a microphysical aerosol effect on clouds. For this, we use the optional two-moment cloud microphysical scheme in COSMO and the online-computed aerosol information for cloud condensation nuclei concentrations (Cccn), replacing the constant Cccn profile. In the radiation scheme, we have implemented a droplet-size-dependent cloud optical depth, allowing now for aerosol-cloud-radiation interactions. To evaluate the models with satellite data, the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) has been implemented. A case study has been carried out to understand the effects of the modifications, where the modified modeling system is applied over the European domain with a horizontal resolution of 0.25° × 0.25°. To reduce the complexity in aerosol-cloud interactions, only warm-phase clouds are considered. We found that the online-coupled aerosol introduces significant changes for some cloud microphysical properties. The cloud effective radius shows an increase of 9.5 %, and the cloud droplet number concentration is reduced by 21.5 %.

The response of filamentary and spherical clouds to the turbulence and magnetic field

NASA Astrophysics Data System (ADS)

Gholipour, Mahmoud

2018-05-01

Recent observations have revealed that there is a power-law relation between magnetic field and density in molecular clouds. Furthermore, turbulence has been observed in some regions of molecular clouds and the velocity dispersion resulting from the turbulence is found to correlate with to the cloud density. Relating to these observations, in this study, we model filamentary and spherical clouds in magnetohydrostatic equilibrium in two quiescent and turbulent regions. The proposed equations are expected to represent the impact of magnetic field and turbulence on the cloud structure and the relation of cloud mass with shape. The Virial theorem is applied to consider the cloud evolution leading to important conditions for equilibrium of the cloud over its lifetime. The obtained results indicate that under the same conditions of the magnetic field and turbulence, each shape presents different responses. The possible ways for the formation of massive cores or coreless clouds in some regions as well as the formation of massive stars or low-mass stars can be discussed based on the results of this study. It should be mentioned that the shape of the clouds plays an important role in the formation of the protostellar clouds as well as their structure and evolution. This role is due to the effects of magnetic fields and turbulence.

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

NASA Astrophysics Data System (ADS)

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, H. A. M.; Svensson, Gunilla; Vaillancourt, Paul A.; Zadra, Ayrton

2016-09-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.

Cognitive Approaches for Medicine in Cloud Computing.

PubMed

Ogiela, Urszula; Takizawa, Makoto; Ogiela, Lidia

2018-03-03

This paper will present the application potential of the cognitive approach to data interpretation, with special reference to medical areas. The possibilities of using the meaning approach to data description and analysis will be proposed for data analysis tasks in Cloud Computing. The methods of cognitive data management in Cloud Computing are aimed to support the processes of protecting data against unauthorised takeover and they serve to enhance the data management processes. The accomplishment of the proposed tasks will be the definition of algorithms for the execution of meaning data interpretation processes in safe Cloud Computing. • We proposed a cognitive methods for data description. • Proposed a techniques for secure data in Cloud Computing. • Application of cognitive approaches for medicine was described.

The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Matsui, T.

2012-01-01

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, a detailed spectral-bin microphysical scheme was 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. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN 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 category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.

Processes that generate and deplete liquid water and snow in thin midlevel mixed-phase clouds

NASA Astrophysics Data System (ADS)

Smith, Adam J.; Larson, Vincent E.; Niu, Jianguo; Kankiewicz, J. Adam; Carey, Lawrence D.

2009-06-01

This paper uses a numerical model to investigate microphysical, radiative, and dynamical processes in mixed-phase altostratocumulus clouds. Three cloud cases are chosen for study, each of which was observed by aircraft during the fifth or ninth Complex Layered Cloud Experiment (CLEX). These three clouds are numerically modeled using large-eddy simulation (LES). The observed and modeled clouds consist of a mixed-phase layer with a quasi-adiabatic profile of liquid, and a virga layer below that consists of snow. A budget of cloud (liquid) water mixing ratio is constructed from the simulations. It shows that large-scale ascent/descent, radiative cooling/heating, turbulent transport, and microphysical processes are all significant. Liquid is depleted indirectly via depositional growth of snow (the Bergeron-Findeisen process). This process is more influential than depletion of liquid via accretional growth of snow. Also constructed is a budget of snow mixing ratio, which turns out to be somewhat simpler. It shows that snow grows by deposition in and below the liquid (mixed-phase) layer, and sublimates in the remainder of the virga region below. The deposition and sublimation are balanced primarily by sedimentation, which transports the snow from the growth region to the sublimation region below. In our three clouds, the vertical extent of the virga layer is influenced more by the profile of saturation ratio below the liquid (mixed-phase) layer than by the mixing ratio of snow at the top of the virga layer.

Process-model simulations of cloud albedo enhancement by aerosols in the Arctic.

PubMed

Kravitz, Ben; Wang, Hailong; Rasch, Philip J; Morrison, Hugh; Solomon, Amy B

2014-12-28

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Process-model simulations of cloud albedo enhancement by aerosols in the Arctic

PubMed Central

Kravitz, Ben; Wang, Hailong; Rasch, Philip J.; Morrison, Hugh; Solomon, Amy B.

2014-01-01

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol–cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. PMID:25404677

Applications integration in a hybrid cloud computing environment: modelling and platform

NASA Astrophysics Data System (ADS)

Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

2013-08-01

With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

Cloud Motion in the GOCI COMS Ocean Colour Data

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Franz, Bryan A.; Mannino, Antonio; Ahn, Jae-Hyun

2016-01-01

The Geostationary Ocean Colour Imager (GOCI) instrument, on Koreas Communications, Oceans, and Meteorological Satellite (COMS), can produce a spectral artefact arising from the motion of clouds the cloud is spatially shifted and the amount of shift varies by spectral band. The length of time it takes to acquire all eight GOCI bands for a given slot (portion of a scene) is sucient to require that cloud motion be taken into account to fully mask or correct the eects of clouds in all bands. Inter-band correlations can be used to measure the amount of cloud shift, which can then be used to adjust the cloud mask so that the union of all shifted masks can act as a mask for all bands. This approach reduces the amount of masking required versus a simple expansion of the mask in all directions away from clouds. Cloud motion can also aect regions with unidentied clouds thin or fractional clouds that evade the cloud identication process yielding degraded quality in retrieved ocean colour parameters. Areas with moving and unidentied clouds require more elaborate masking algo-rithms to remove these degraded retrievals. Correction for the eects of moving fractional clouds may also be possible. The cloud shift information can be used to determine cloud motion and thus wind at the cloud levels on sub-minute timescales. The benecial and negative eects of moving clouds should be con-sidered for any ocean colour instrument design and associated data processing plans.

Measurement needs guided by synthetic radar scans in high-resolution model output

NASA Astrophysics Data System (ADS)

Varble, A.; Nesbitt, S. W.; Borque, P.

2017-12-01

Microphysical and dynamical process interactions within deep convective clouds are not well understood, partly because measurement strategies often focus on statistics of cloud state rather than cloud processes. While processes cannot be directly measured, they can be inferred with sufficiently frequent and detailed scanning radar measurements focused on the life cycleof individual cloud regions. This is a primary goal of the 2018-19 DOE ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) and NSF Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaigns in central Argentina, where orographic deep convective initiation is frequent with some high-impact systems growing into the tallest and largest in the world. An array of fixed and mobile scanning multi-wavelength dual-polarization radars will be coupled with surface observations, sounding systems, multi-wavelength vertical profilers, and aircraft in situ measurements to characterize convective cloud life cycles and their relationship with environmental conditions. While detailed cloud processes are an observational target, the radar scan patterns that are most ideal for observing them are unclear. They depend on the locations and scales of key microphysical and dynamical processes operating within the cloud. High-resolution simulations of clouds, while imperfect, can provide information on these locations and scales that guide radar measurement needs. Radar locations are set in the model domain based on planned experiment locations, and simulatedorographic deep convective initiation and upscale growth are sampled using a number of different scans involving RHIs or PPIs with predefined elevation and azimuthal angles that approximately conform with radar range and beam width specifications. Each full scan pattern is applied to output atsingle model time steps with time step intervals that depend on the length of time required to complete each scan in the real world. The ability of different scans to detect key processes within the convective cloud life cycle are examined in connection with previous and subsequent dynamical and microphysical transitions. This work will guide strategic scan patterns that will be used during CACTI and RELAMPAGO.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.