Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

NASA Astrophysics Data System (ADS)

Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

2018-04-01

Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the vertical distribution of particle sizes, which allow reconstructing the profile of reff close to the cloud top. The comparison between retrieved and in situ reff yields a normalized mean absolute deviation, which ranges between 1.5 and 10.3 %, and a robust correlation coefficient of 0.82.

Droplet Size Distributions as a function of rainy system type and Cloud Condensation Nuclei concentrations

NASA Astrophysics Data System (ADS)

Cecchini, Micael A.; Machado, Luiz A. T.; Artaxo, Paulo

2014-06-01

This work aims to study typical Droplet Size Distributions (DSDs) for different types of precipitation systems and Cloud Condensation Nuclei concentrations over the Vale do Paraíba region in southeastern Brazil. Numerous instruments were deployed during the CHUVA (Cloud processes of tHe main precipitation systems in Brazil: a contribUtion to cloud resolVing modeling and to the GPM) Project in Vale do Paraíba campaign, from November 22, 2011 through January 10, 2012. Measurements of CCN (Cloud Condensation Nuclei) and total particle concentrations, along with measurements of rain DSDs and standard atmospheric properties, including temperature, pressure and wind intensity and direction, were specifically made in this study. The measured DSDs were parameterized with a gamma function using the moment method. The three gamma parameters were disposed in a 3-dimensional space, and subclasses were classified using cluster analysis. Seven DSD categories were chosen to represent the different types of DSDs. The DSD classes were useful in characterizing precipitation events both individually and as a group of systems with similar properties. The rainfall regime classification system was employed to categorize rainy events as local convective rainfall, organized convection rainfall and stratiform rainfall. Furthermore, the frequencies of the seven DSD classes were associated to each type of rainy event. The rainfall categories were also employed to evaluate the impact of the CCN concentration on the DSDs. In the stratiform rain events, the polluted cases had a statistically significant increase in the total rain droplet concentrations (TDCs) compared to cleaner events. An average concentration increase from 668 cm- 3 to 2012 cm- 3 for CCN at 1% supersaturation was found to be associated with an increase of approximately 87 m- 3 in TDC for those events. For the local convection cases, polluted events presented a 10% higher mass weighted mean diameter (Dm) on average. For the organized convection events, no significant results were found.

On the Onset of the Rainy Season in Amazonia: WHAT the Observations Show, and Why the Biases in Climate Models?

NASA Astrophysics Data System (ADS)

Marengo, J. A.; Alves, L. M.; Fu, R.

2014-12-01

The onset of the Amazon rainy season shows a large temporal and spatial variability, delays on the date of the onset will have strong impacts on local agriculture, hydroelectric power generation as well as on the hydrology of large rivers. Two "once-in-a-century" droughts occurred in 2005 and 2010, and it was shown that in those events the rainy season started later than normal, and also that on the last 10 years the dry season has increased in length by about one month. These events highlight the urgency for improving our understanding and capability to model onset of the rainy season and drought variability, for the present and future. Most studies have attributed the variability of the rainy season onset over Amazonia to the variability of the tropical oceans whether other factors, such as climate change, land use and aerosols also contribute to the variability are not clear.. Global climate models run on seasonal climate forecast mode still show large uncertainties on the prediction of onset of seasonal rains. As for climate change, the CMIP3 and CMIP5 appear to underestimate the past variability, and also project virtually no future change of the onset of rainy season over the Amazon even when they are forced by strong greenhouse forcing under the RCP8.5 emission scenario. Why these models underestimate the variability of the rainy season onset, and whether this bias implies an underestimate of sensitivity of their dry season length to anthropogenic radiative forcing remain unclear. This FAPESP DOE grant 2013/50538 aims to explore use of the measurements provided by the Atmospheric Radiation Measurement (ARM) Mobile Facilities (AMF)-GoAmazon and the Cloud processes of the main precipitation systems in Brazil (CHUVA) Field Experiments, along with global and regional model experiments, to explore the sources of the above described uncertainty. The project will address several issues, i.e. the inadequate representation of the types of convection (i.e., maritime versus continental) and their relationships to aerosols, land surface and atmospheric circulation as represented in climate models We will present our initial results addressing the factors that control the variability of the wet season onset over Amazonia, the influence of convective types on atmospheric diabatic heating based on GoAmazon and CHUVA.

Sensor de orvalho/chuva aplicado à operação de telescópios

NASA Astrophysics Data System (ADS)

Raffaelli, J. C.; Neres, N. L.; Strauss, C.

2003-08-01

Foi desenvolvida uma estação meteorológica para o telescópio robótico Obelix do Observatório Abrahão de Moraes que inclui sensores de temperatura e umidade, além de um inédito sensor de orvalho e chuva que comanda o fechamento automático da cúpula caso haja perigo de condensação. Este sensor é composto de uma malha de segmentos metálicos próximos e detecta o aumento da condutividade do ar que precede a condensação. Esse método é mais confiável que o critério de 100% de umidade, que pode causar falsos alarmes devido a imprecisão dos sensores de umidade em geral e por não considerar a influência dos ventos que dificultam a condensação. O trabalho apresenta o método de construção desse sensor e os testes de avaliação. Sugere-se portanto a inclusão desse sensor nas estações meteorológicas dos telescópios do país.

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.

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.

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.

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.

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.

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.

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.

Evolution of the Planetary Boundary Layer on the northern coast of Brazil during the CHUVA campaign

NASA Astrophysics Data System (ADS)

Ramos, Diogo Nunes da Silva; Fernandez, Julio Pablo Reyes; Fisch, Gilberto

2018-05-01

This study aims to characterize the wind and thermodynamic structure of the Planetary Boundary Layer (PBL) on the northern coast of Brazil (NCB) via the CHUVA datasets. Three synoptic conditions were present in the NCB region between March 1 and 25, 2010: a dry period, the Upper Tropospheric Cyclonic Vortex (UTCV) and the Intertropical Convergence Zone (ITCZ). Nighttime precipitation accounted for 78% of the total precipitation observed in the month, mainly during the ITCZ. In general, the surface meteorological fields were few changed by intense weather events due to proximity to the ocean and the predominant contribution of the northeasterly trade winds. There was also a weak sea breeze signal that maintained the horizontal moisture flow in the studied area. On dry days, the PBL depth was higher, drier, and warmer, resulting in stronger winds below 500 m. Moreover, trends throughout the period suggest that PBLs are near-neutral below 500 m. However, the wind variability was intensified by up to 20% due to downdrafts and higher wind shears during the deep convection mechanisms derived by UTCV. Furthermore, ITCZ mixed rainfall cooled the PBL at approximately 2 K, making it very stable according to the Richardson number classification adopted. The observed temporal and spatial scale represent challenges to the physical parameterizations used to improve numerical weather prediction models over tropical coastal areas.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Representation of Arctic mixed-phase clouds and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a cloud-resolving study

NASA Astrophysics Data System (ADS)

Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei

2011-01-01

Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, regimes of cloud particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase clouds are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform cloud but the WBF process occurs in about 50% of cloud volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

Coupling Spectral-bin Cloud Microphysics with the MOSAIC Aerosol Model in WRF-Chem: Methodology and Results for Marine Stratocumulus Clouds

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

Gao, Wenhua; Fan, Jiwen; Easter, Richard C.

Aerosol-cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol-cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF-Chem) at convection-permitting scales by coupling spectral-bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces themore » treatments in the original SBM. It also includes the modified aerosol resuspension and in-cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full-chemistry. We compare the aerosol activation process in the newly-coupled SBM-MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM-MOSAIC with full-chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two-moment microphysics.« less

Coupling spectral-bin cloud microphysics with the MOSAIC aerosol model in WRF-Chem: Methodology and results for marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Gao, Wenhua; Fan, Jiwen; Easter, R. C.; Yang, Qing; Zhao, Chun; Ghan, Steven J.

2016-09-01

Aerosol-cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol-cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF-Chem) at convection-permitting scales by coupling spectral-bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces the treatments in the original SBM. It also includes the modified aerosol resuspension and in-cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full-chemistry. We compare the aerosol activation process in the newly coupled SBM-MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM-MOSAIC with full-chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two-moment microphysics.

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.

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.

Multi-scale Modeling of Arctic Clouds

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

2017-12-01

The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

NASA Astrophysics Data System (ADS)

Sednev, I.; Menon, S.; McFarquhar, G.

2008-06-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9th-10th October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and undersaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

NASA Astrophysics Data System (ADS)

Sednev, I.; Menon, S.; McFarquhar, G.

2009-07-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9-10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

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.

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

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.

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.

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

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 ...

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.

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.

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

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.

Parameterization of cloud lidar backscattering profiles by means of asymmetrical Gaussians

NASA Astrophysics Data System (ADS)

del Guasta, Massimo; Morandi, Marco; Stefanutti, Leopoldo

1995-06-01

A fitting procedure for cloud lidar data processing is shown that is based on the computation of the first three moments of the vertical-backscattering (or -extinction) profile. Single-peak clouds or single cloud layers are approximated to asymmetrical Gaussians. The algorithm is particularly stable with respect to noise and processing errors, and it is much faster than the equivalent least-squares approach. Multilayer clouds can easily be treated as a sum of single asymmetrical Gaussian peaks. The method is suitable for cloud-shape parametrization in noisy lidar signatures (like those expected from satellite lidars). It also permits an improvement of cloud radiative-property computations that are based on huge lidar data sets for which storage and careful examination of single lidar profiles can't be carried out.

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.

Evidence of Chemical Cloud Processing from In Situ Measurements in the Polluted Marine Environment

NASA Astrophysics Data System (ADS)

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

2017-12-01

Chemical cloud processing alters activated cloud condensation nuclei (CCN). Aqueous oxidation of trace gases dissolved within cloud droplets adds soluble material. As most cloud droplets evaporate, the residual material produces CCN that are larger and with a different hygroscopicity (κ). This improves the CCN, lowering the critical supersaturation (Sc), making it more easily activated. This process separates the processed (accumulation) and unprocessed (Aitken) modes creating bimodal CCN distributions (Hudson et al., 2015). Various measurements made during the MArine Stratus/stratocumulus Experiment (MASE), including CCN, exhibited aqueous processing signals. Particle size distributions; measured by a differential mobility analyzer; were compared with CCN distributions; measured by the Desert Research Institute CCN spectrometer; by converting size to Sc using κ to overlay concurrent distributions. By tuning each mode to the best agreement, κ for each mode is determined; processed κ (κp), unprocessed κ (κu). In MASE, 59% of bimodal distributions had different κ for the two modes indicating dominance of chemical processing via aqueous oxidation. This is consistent with Hudson et al. (2015). Figure 1A also indicates chemical processing with larger κp between 0.35-0.75. Processed CCN had an influx of soluble material from aqueous oxidation which increased κp versus κu. Above 0.75 κp is lower than κu (Fig. 1A). When κu is high and sulfate material is added, κp tends towards κ of the added material. Thus, κp is reduced by additional material that is less soluble than the original material. Chemistry measurements in MASE also indicate in-cloud aqueous oxidation (Fig. 1B and 1C). Higher fraction of CCN concentrations in the processed mode are also associated with larger amounts of sulfates (Fig. 1B, red) and nitrates (Fig. 1C, orange) while SO2 (Fig. 1B, black) and O3 (Fig. 1C, blue) have lower amounts. This larger amount of sulfate is at the expense of SO2, indicating aqueous oxidation within cloud as associated with larger concentrations in the processed mode. Thus, in situ measurements indicate that chemical cloud processing alters size, Sc and κ of activated CCN. Hudson et al. (2015), JGRA, 120, 3436-3452.

Polarimetric radar and aircraft observations of saggy bright bands during MC3E

DOE PAGES

Matthew R. Kumjian; Giangrande, Scott E.; Mishra, Subashree; ...

2016-03-19

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.

Research on Quantum Authentication Methods for the Secure Access Control Among Three Elements of Cloud Computing

NASA Astrophysics Data System (ADS)

Dong, Yumin; Xiao, Shufen; Ma, Hongyang; Chen, Libo

2016-12-01

Cloud computing and big data have become the developing engine of current information technology (IT) as a result of the rapid development of IT. However, security protection has become increasingly important for cloud computing and big data, and has become a problem that must be solved to develop cloud computing. The theft of identity authentication information remains a serious threat to the security of cloud computing. In this process, attackers intrude into cloud computing services through identity authentication information, thereby threatening the security of data from multiple perspectives. Therefore, this study proposes a model for cloud computing protection and management based on quantum authentication, introduces the principle of quantum authentication, and deduces the quantum authentication process. In theory, quantum authentication technology can be applied in cloud computing for security protection. This technology cannot be cloned; thus, it is more secure and reliable than classical methods.

Approaches to Observe Anthropogenic Aerosol-Cloud Interactions.

PubMed

Quaas, Johannes

Anthropogenic aerosol particles exert an-quantitatively very uncertain-effective radiative forcing due to aerosol-cloud interactions via an immediate altering of cloud albedo on the one hand and via rapid adjustments by alteration of cloud processes and by changes in thermodynamic profiles on the other hand. Large variability in cloud cover and properties and the therefore low signal-to-noise ratio for aerosol-induced perturbations hamper the identification of effects in observations. Six approaches are discussed as a means to isolate the impact of anthropogenic aerosol on clouds from natural cloud variability to estimate or constrain the effective forcing. These are (i) intentional cloud modification, (ii) ship tracks, (iii) differences between the hemispheres, (iv) trace gases, (v) weekly cycles and (vi) trends. Ship track analysis is recommendable for detailed process understanding, and the analysis of weekly cycles and long-term trends is most promising to derive estimates or constraints on the effective radiative forcing.

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

2005-01-01

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Security Risks of Cloud Computing and Its Emergence as 5th Utility Service

NASA Astrophysics Data System (ADS)

Ahmad, Mushtaq

Cloud Computing is being projected by the major cloud services provider IT companies such as IBM, Google, Yahoo, Amazon and others as fifth utility where clients will have access for processing those applications and or software projects which need very high processing speed for compute intensive and huge data capacity for scientific, engineering research problems and also e- business and data content network applications. These services for different types of clients are provided under DASM-Direct Access Service Management based on virtualization of hardware, software and very high bandwidth Internet (Web 2.0) communication. The paper reviews these developments for Cloud Computing and Hardware/Software configuration of the cloud paradigm. The paper also examines the vital aspects of security risks projected by IT Industry experts, cloud clients. The paper also highlights the cloud provider's response to cloud security risks.

Big data processing in the cloud - Challenges and platforms

NASA Astrophysics Data System (ADS)

Zhelev, Svetoslav; Rozeva, Anna

2017-12-01

Choosing the appropriate architecture and technologies for a big data project is a difficult task, which requires extensive knowledge in both the problem domain and in the big data landscape. The paper analyzes the main big data architectures and the most widely implemented technologies used for processing and persisting big data. Clouds provide for dynamic resource scaling, which makes them a natural fit for big data applications. Basic cloud computing service models are presented. Two architectures for processing big data are discussed, Lambda and Kappa architectures. Technologies for big data persistence are presented and analyzed. Stream processing as the most important and difficult to manage is outlined. The paper highlights main advantages of cloud and potential problems.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

Millimeter- and Submillimeter-Wave Remote Sensing Using Small Satellites

NASA Technical Reports Server (NTRS)

Ehsan, N.; Esper, J.; Piepmeier, J.; Racette, P.; Wu, D.

2014-01-01

Cloud ice properties and processes play fundamental roles in atmospheric radiation and precipitation. Limited knowledge and poor representation of clouds in global climate models have led to large uncertainties about cloud feedback processes under climate change. Ice clouds have been used as a tuning parameter in the models to force agreement with observations of the radiation budget at the top of the atmosphere, and precipitation at the bottom. The lack of ice cloud measurements has left the cloud processes at intermediate altitudes unconstrained. Millimeter (mm) and submillimeter (submm)-wave radiometry is widely recognized for its potential to fill the cloud measurement gap in the middle and upper troposphere. Analyses have shown that channels from 183900 GHz offer good sensitivity to ice cloud scattering and can provide ice water path (IWP) products to an accuracy of 25 by simultaneously retrieving ice particle size (Dme) and IWP. Therefore, it is highly desirable to develop a cost-effective, compact mm/submm-wave instrument for cloud observations that can be deployed on future small satellites.This paper presents a conceptual study for a mm/submm-wave instrument for multispectral measurements of ice clouds. It discusses previous work at these frequencies by NASA Goddard Space Flight Center (GSFC) and the current instrument study, as well as receiver architectures and their anticipated performance. And finally, it describes a microsatellite prototype intended for use with this mm/submm-wave instrument.

Characterization of cumulus cloud fields using trajectories in the center of gravity versus water mass phase space: 2. Aerosol effects on warm convective clouds: Center of Gravity Versus Water Mass 2

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

Heiblum, Reuven H.; Altaratz, Orit; Koren, Ilan

2016-06-07

In Part I of this work a 3D cloud tracking algorithm and phase-space of center of gravity altitude versus cloud liquid water mass (CvM space) were introduced and described in detail. We showed how new physical insight can be gained by following cloud trajectories in the CvM space. Here, this approach is used to investigate aerosol effects on cloud fields of warm cumuli. We show a clear effect of the aerosol loading on the shape and size of CvM clusters. We also find fundamental differences in the CvM space between simulations using bin versus bulk microphysical schemes, with the binmore » scheme precipitation expressing much higher sensitivity to changes in aerosol concentrations. Using the bin microphysical scheme, we find that the increase in cloud center of gravity altitude with increase in aerosol concentrations occurs for a wide range of cloud sizes. This is attributed to reduced sedimentation, increased buoyancy and vertical velocities, and increased environmental instability, all of which are tightly coupled to inhibition of precipitation processes and subsequent feedbacks of clouds on their environment. Many of the physical processes shown here are consistent with processes typically associated with cloud invigoration.« less

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

PubMed

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

2017-08-11

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

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

PubMed Central

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

2017-01-01

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

H2O2 modulates the energetic metabolism of the cloud microbiome

NASA Astrophysics Data System (ADS)

Wirgot, Nolwenn; Vinatier, Virginie; Deguillaume, Laurent; Sancelme, Martine; Delort, Anne-Marie

2017-12-01

Chemical reactions in clouds lead to oxidation processes driven by radicals (mainly HO⚫, NO3⚫, or HO2⚫) or strong oxidants such as H2O2, O3, nitrate, and nitrite. Among those species, hydrogen peroxide plays a central role in the cloud chemistry by driving its oxidant capacity. In cloud droplets, H2O2 is transformed by microorganisms which are metabolically active. Biological activity can therefore impact the cloud oxidant capacity. The present article aims at highlighting the interactions between H2O2 and microorganisms within the cloud system. First, experiments were performed with selected strains studied as a reference isolated from clouds in microcosms designed to mimic the cloud chemical composition, including the presence of light and iron. Biotic and abiotic degradation rates of H2O2 were measured and results showed that biodegradation was the most efficient process together with the photo-Fenton process. H2O2 strongly impacted the microbial energetic state as shown by adenosine triphosphate (ATP) measurements in the presence and absence of H2O2. This ATP depletion was not due to the loss of cell viability. Secondly, correlation studies were performed based on real cloud measurements from 37 cloud samples collected at the PUY station (1465 m a.s.l., France). The results support a strong correlation between ATP and H2O2 concentrations and confirm that H2O2 modulates the energetic metabolism of the cloud microbiome. The modulation of microbial metabolism by H2O2 concentration could thus impact cloud chemistry, in particular the biotransformation rates of carbon compounds, and consequently can perturb the way the cloud system is modifying the global atmospheric chemistry.

A modeling study of marine boundary layer clouds

NASA Technical Reports Server (NTRS)

Wang, Shouping; Fitzjarrald, Daniel E.

1993-01-01

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

Modeling of the Wegener Bergeron Findeisen process—implications for aerosol indirect effects

NASA Astrophysics Data System (ADS)

Storelvmo, T.; Kristjánsson, J. E.; Lohmann, U.; Iversen, T.; Kirkevåg, A.; Seland, Ø.

2008-10-01

A new parameterization of the Wegener-Bergeron-Findeisen (WBF) process has been developed, and implemented in the general circulation model CAM-Oslo. The new parameterization scheme has important implications for the process of phase transition in mixed-phase clouds. The new treatment of the WBF process replaces a previous formulation, in which the onset of the WBF effect depended on a threshold value of the mixing ratio of cloud ice. As no observational guidance for such a threshold value exists, the previous treatment added uncertainty to estimates of aerosol effects on mixed-phase clouds. The new scheme takes subgrid variability into account when simulating the WBF process, allowing for smoother phase transitions in mixed-phase clouds compared to the previous approach. The new parameterization yields a model state which gives reasonable agreement with observed quantities, allowing for calculations of aerosol effects on mixed-phase clouds involving a reduced number of tunable parameters. Furthermore, we find a significant sensitivity to perturbations in ice nuclei concentrations with the new parameterization, which leads to a reversal of the traditional cloud lifetime effect.

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

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

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

Hybrid Pluggable Processing Pipeline (HyP3): Programmatic Access to Cloud-Based Processing of SAR Data

NASA Astrophysics Data System (ADS)

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

2017-12-01

A problem often faced by Earth science researchers is the question of how to scale algorithms that were developed against few datasets and take them to regional or global scales. This problem only gets worse as we look to a future with larger and larger datasets becoming available. One significant hurdle can be having the processing and storage resources available for such a task, not to mention the administration of those resources. As a processing environment, the cloud offers nearly unlimited potential for compute and storage, with limited administration required. The goal of the Hybrid Pluggable Processing Pipeline (HyP3) project was to demonstrate the utility of the Amazon cloud to process large amounts of data quickly and cost effectively. Principally built by three undergraduate students at the ASF DAAC, the HyP3 system relies on core Amazon cloud services such as Lambda, Relational Database Service (RDS), Elastic Compute Cloud (EC2), Simple Storage Service (S3), and Elastic Beanstalk. HyP3 provides an Application Programming Interface (API) through which users can programmatically interface with the HyP3 system; allowing them to monitor and control processing jobs running in HyP3, and retrieve the generated HyP3 products when completed. This presentation will focus on the development techniques and enabling technologies that were used in developing the HyP3 system. Data and process flow, from new subscription through to order completion will be shown, highlighting the benefits of the cloud for each step. Because the HyP3 system can be accessed directly from a user's Python scripts, powerful applications leveraging SAR products can be put together fairly easily. This is the true power of HyP3; allowing people to programmatically leverage the power of the cloud.

The Cloud Ice Mountain Experiment (CIME) 1998: experiment overview and modelling of the microphysical processes during the seeding by isentropic gas expansion

NASA Astrophysics Data System (ADS)

Wobrock, Wolfram; Flossmann, Andrea I.; Monier, Marie; Pichon, Jean-Marc; Cortez, Laurent; Fournol, Jean-François; Schwarzenböck, Alfons; Mertes, Stephan; Heintzenberg, Jost; Laj, Paolo; Orsi, Giordano; Ricci, Loretta; Fuzzi, Sandro; Brink, Harry Ten; Jongejan, Piet; Otjes, René

The second field campaign of the Cloud Ice Mountain Experiment (CIME) project took place in February 1998 on the mountain Puy de Dôme in the centre of France. The content of residual aerosol particles, of H 2O 2 and NH 3 in cloud droplets was evaluated by evaporating the drops larger than 5 μm in a Counterflow Virtual Impactor (CVI) and by measuring the residual particle concentration and the released gas content. The same trace species were studied behind a round jet impactor for the complementary interstitial aerosol particles smaller than 5 μm diameter. In a second step of experiments, the ambient supercooled cloud was converted to a mixed phase cloud by seeding the cloud with ice particles by the gas release from pressurised gas bottles. A comparison between the physical and chemical characteristics of liquid drops and ice particles allows a study of the fate of the trace constituents during the presence of ice crystals in the cloud. In the present paper, an overview is given of the CIME 98 experiment and the instrumentation deployed. The meteorological situation during the experiment was analysed with the help of a cloud scale model. The microphysics processes and the behaviour of the scavenged aerosol particles before and during seeding are analysed with the detailed microphysical model ExMix. The simulation results agreed well with the observations and confirmed the assumption that the Bergeron-Findeisen process was dominating during seeding and was influencing the partitioning of aerosol particles between drops and ice crystals. The results of the CIME 98 experiment give an insight on microphysical changes, redistribution of aerosol particles and cloud chemistry during the Bergeron-Findeisen process when acting also in natural clouds.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.

Satellite Data Analysis of Impact of Anthropogenic Air Pollution on Ice Clouds

NASA Astrophysics Data System (ADS)

Gu, Y.; Liou, K. N.; Zhao, B.; Jiang, J. H.; Su, H.

2017-12-01

Despite numerous studies about the impact of aerosols on ice clouds, the role of anthropogenic aerosols in ice processes, especially over pollution regions, remains unclear and controversial, and has not been considered in a regional model. The objective of this study is to improve our understanding of the ice process associated with anthropogenic aerosols, and provide a comprehensive assessment of the contribution of anthropogenic aerosols to ice nucleation, ice cloud properties, and the consequent regional radiative forcing. As the first attempt, we evaluate the effects of different aerosol types (mineral dust, air pollution, polluted dust, and smoke) on ice cloud micro- and macro-physical properties using satellite data. We identify cases with collocated CloudSat, CALIPSO, and Aqua observations of vertically resolved aerosol and cloud properties, and process these observations into the same spatial resolution. The CALIPSO's aerosol classification algorithm determines aerosol layers as one of six defined aerosol types by taking into account the lidar depolarization ratio, integrated attenuated backscattering, surface type, and layer elevation. We categorize the cases identified above according to aerosol types, collect relevant aerosol and ice cloud variables, and determine the correlation between column/layer AOD and ice cloud properties for each aerosol type. Specifically, we investigate the correlation between aerosol loading (indicated by the column AOD and layer AOD) and ice cloud microphysical properties (ice water content, ice crystal number concentration, and ice crystal effective radius) and macro-physical properties (ice water path, ice cloud fraction, cloud top temperature, and cloud thickness). By comparing the responses of ice cloud properties to aerosol loadings for different aerosol types, we infer the role of different aerosol types in ice nucleation and the evolution of ice clouds. Our preliminary study shows that changes in the ice crystal effective radius with respect to AOD over Eastern Asia for the aerosol types of polluted continental and mineral dust look similar, implying that both air pollution and mineral dust could affect the microphysical properties of ice clouds.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

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

The effect of aerosol-derived changes in the warm phase on the properties of deep convective clouds

NASA Astrophysics Data System (ADS)

Chen, Qian; Koren, Ilan; Altaratz, Orit; Heiblum, Reuven; Dagan, Guy

2017-04-01

The aerosol impact on deep convective clouds starts in an increased number of cloud droplets in higher aerosol loading environment. This change drives many others, like enhanced condensational growth, delay in collision-coalescence and others. Since the warm processes serve as the initial and boundary conditions for the mixed and cold-phase processes in deep clouds, it is highly important to understand the aerosol effect on them. The weather research and forecasting model (WRF) with spectral bin microphysics was used to study a deep convective system over the Marshall Islands, during the Kwajalein Experiment (KWAJEX). Three simulations were conducted with aerosol concentrations of 100, 500 and 2000 cm-3, to reflect clean, semipolluted, and polluted conditions. The results of the clean run agreed well with the radar profiles and rain rate observations. The more polluted simulations resulted in larger total cloud mass, larger upper level cloud fraction and rain rates. There was an increased mass both below and above the zero temperature level. It indicates of more efficient growth processes both below and above the zero level. In addition the polluted runs showed an increased upward transport (across the zero level) of liquid water due to both stronger updrafts and larger droplet mobility. In this work we discuss the transport of cloud mass crossing the zero temperature level (in both directions) in order to gain a process level understanding of how aerosol effects on the warm processes affect the macro- and micro-properties of deep convective clouds.

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

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

Woods, Sarah

2015-12-01

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

Satellite Studies of Cirrus Clouds for Project Fire

NASA Technical Reports Server (NTRS)

1997-01-01

Examine global cloud climatologies for evidence of human caused changes in cloud cover and their effect on the Earth's heat budget through radiative processes. Quantify climatological changes in global cloud cover and estimate their effect on the Earth's heat budget. Improve our knowledge of global cloud cover and its changes through the merging of several satellite data sets.

Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform

NASA Astrophysics Data System (ADS)

Shi, Cheng; Liu, Fang; Li, Ling-Ling; Hao, Hong-Xia

2014-01-01

The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.

Formation of highly porous aerosol particles by atmospheric freeze-drying in ice clouds

PubMed Central

Adler, Gabriela; Koop, Thomas; Haspel, Carynelisa; Taraniuk, Ilya; Moise, Tamar; Koren, Ilan; Heiblum, Reuven H.; Rudich, Yinon

2013-01-01

The cycling of atmospheric aerosols through clouds can change their chemical and physical properties and thus modify how aerosols affect cloud microphysics and, subsequently, precipitation and climate. Current knowledge about aerosol processing by clouds is rather limited to chemical reactions within water droplets in warm low-altitude clouds. However, in cold high-altitude cirrus clouds and anvils of high convective clouds in the tropics and midlatitudes, humidified aerosols freeze to form ice, which upon exposure to subsaturation conditions with respect to ice can sublimate, leaving behind residual modified aerosols. This freeze-drying process can occur in various types of clouds. Here we simulate an atmospheric freeze-drying cycle of aerosols in laboratory experiments using proxies for atmospheric aerosols. We find that aerosols that contain organic material that undergo such a process can form highly porous aerosol particles with a larger diameter and a lower density than the initial homogeneous aerosol. We attribute this morphology change to phase separation upon freezing followed by a glass transition of the organic material that can preserve a porous structure after ice sublimation. A porous structure may explain the previously observed enhancement in ice nucleation efficiency of glassy organic particles. We find that highly porous aerosol particles scatter solar light less efficiently than nonporous aerosol particles. Using a combination of satellite and radiosonde data, we show that highly porous aerosol formation can readily occur in highly convective clouds, which are widespread in the tropics and midlatitudes. These observations may have implications for subsequent cloud formation cycles and aerosol albedo near cloud edges. PMID:24297908

Formation of highly porous aerosol particles by atmospheric freeze-drying in ice clouds.

PubMed

Adler, Gabriela; Koop, Thomas; Haspel, Carynelisa; Taraniuk, Ilya; Moise, Tamar; Koren, Ilan; Heiblum, Reuven H; Rudich, Yinon

2013-12-17

The cycling of atmospheric aerosols through clouds can change their chemical and physical properties and thus modify how aerosols affect cloud microphysics and, subsequently, precipitation and climate. Current knowledge about aerosol processing by clouds is rather limited to chemical reactions within water droplets in warm low-altitude clouds. However, in cold high-altitude cirrus clouds and anvils of high convective clouds in the tropics and midlatitudes, humidified aerosols freeze to form ice, which upon exposure to subsaturation conditions with respect to ice can sublimate, leaving behind residual modified aerosols. This freeze-drying process can occur in various types of clouds. Here we simulate an atmospheric freeze-drying cycle of aerosols in laboratory experiments using proxies for atmospheric aerosols. We find that aerosols that contain organic material that undergo such a process can form highly porous aerosol particles with a larger diameter and a lower density than the initial homogeneous aerosol. We attribute this morphology change to phase separation upon freezing followed by a glass transition of the organic material that can preserve a porous structure after ice sublimation. A porous structure may explain the previously observed enhancement in ice nucleation efficiency of glassy organic particles. We find that highly porous aerosol particles scatter solar light less efficiently than nonporous aerosol particles. Using a combination of satellite and radiosonde data, we show that highly porous aerosol formation can readily occur in highly convective clouds, which are widespread in the tropics and midlatitudes. These observations may have implications for subsequent cloud formation cycles and aerosol albedo near cloud edges.

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.

Pointo - a Low Cost Solution to Point Cloud Processing

NASA Astrophysics Data System (ADS)

Houshiar, H.; Winkler, S.

2017-11-01

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

Simulating the Current Water Cycle with the NASA Ames Mars Global Climate Model

NASA Astrophysics Data System (ADS)

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

2017-12-01

The water cycle is a critical component of the current Mars climate system, and it is now widely recognized that water ice clouds significantly affect the nature of the simulated water cycle. Two processes are key to implementing clouds in a Mars global climate model (GCM): the microphysical processes of formation and dissipation, and their radiative effects on atmospheric heating/cooling rates. Together, these processes alter the thermal structure, change the atmospheric dynamics, and regulate inter-hemispheric transport. We have made considerable progress using the NASA Ames Mars GCM to simulate the current-day water cycle with radiatively active clouds. Cloud fields from our baseline simulation are in generally good agreement with observations. The predicted seasonal extent and peak IR optical depths are consistent MGS/TES observations. Additionally, the thermal response to the clouds in the aphelion cloud belt (ACB) is generally consistent with observations and other climate model predictions. Notably, there is a distinct gap in the predicted clouds over the North Residual Cap (NRC) during local summer, but the clouds reappear in this simulation over the NRC earlier than the observations indicate. Polar clouds are predicted near the seasonal CO2 ice caps, but the column thicknesses of these clouds are generally too thick compared to observations. Our baseline simulation is dry compared to MGS/TES-observed water vapor abundances, particularly in the tropics and subtropics. These areas of disagreement appear to be a consistent with other current water cycle GCMs. Future avenues of investigation will target improving our understanding of what controls the vertical extent of clouds and the apparent seasonal evolution of cloud particle sizes within the ACB.

Aerosol Processing in Mixed-Phase Clouds in ECHAM5-HAM: Comparison of Single-Column Model Simulations to Observations

NASA Astrophysics Data System (ADS)

Hoose, C.; Lohmann, U.; Stier, P.; Verheggen, B.; Weingartner, E.; Herich, H.

2007-12-01

The global aerosol-climate model ECHAM5-HAM (Stier et al., 2005) 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 (Lohmann et al., 2007). 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) (Verheggen et al, 2007). Although the single-column simulations can not 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 forcing non-equilibrium conditions. References: U. Lohmann et al., Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM, Atmos. Chem. Phys. 7, 3425-3446 (2007) P. Stier et al., The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys. 5, 1125-1156 (2005) B. Verheggen et al., Aerosol partitioning between the interstitial and the condensed phase in mixed-phase clouds, Accepted for publication in J. Geophys. Res. (2007)

Generic-distributed framework for cloud services marketplace based on unified ontology.

PubMed

Hasan, Samer; Valli Kumari, V

2017-11-01

Cloud computing is a pattern for delivering ubiquitous and on demand computing resources based on pay-as-you-use financial model. Typically, cloud providers advertise cloud service descriptions in various formats on the Internet. On the other hand, cloud consumers use available search engines (Google and Yahoo) to explore cloud service descriptions and find the adequate service. Unfortunately, general purpose search engines are not designed to provide a small and complete set of results, which makes the process a big challenge. This paper presents a generic-distrusted framework for cloud services marketplace to automate cloud services discovery and selection process, and remove the barriers between service providers and consumers. Additionally, this work implements two instances of generic framework by adopting two different matching algorithms; namely dominant and recessive attributes algorithm borrowed from gene science and semantic similarity algorithm based on unified cloud service ontology. Finally, this paper presents unified cloud services ontology and models the real-life cloud services according to the proposed ontology. To the best of the authors' knowledge, this is the first attempt to build a cloud services marketplace where cloud providers and cloud consumers can trend cloud services as utilities. In comparison with existing work, semantic approach reduced the execution time by 20% and maintained the same values for all other parameters. On the other hand, dominant and recessive attributes approach reduced the execution time by 57% but showed lower value for recall.

Stratocumulus Precipitation and Entrainment Experiment (SPEE) Field Campaign Report

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

Albrecht, Bruce; Ghate, Virendra; CADeddu, Maria

2016-06-01

The scientific focus of this project was to examine precipitation and entrainment processes in marine stratocumulus clouds. The entrainment studies focused on characterizing cloud turbulence at cloud top using Doppler cloud radar observations. The precipitation studies focused on characterizing the precipitation and the macroscopic properties (cloud thickness, and liquid water path) of the clouds. This project will contribute to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s overall objective of providing the remote-sensing observations needed to improve the representation of key cloud processes in climate models. It will be of direct relevance to the componentsmore » of ARM dealing with entrainment and precipitation processes in stratiform clouds. Further, the radar observing techniques that will be used in this study were developed using ARM Southern Great Plains (SGP) facility observations under Atmospheric System Research (ASR) support. The observing systems operating automatously from a site located just north of the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) aircraft hangar in Marina, California during the period of 1 May to 4 November 2015 included: 1. Microwave radiometer: ARM Microwave Radiometer, 3-Channel (MWR3C) with channels centered at 23.834, 30, and 89 GHz; supported by Dr. Maria Cadeddu. 2. Cloud Radar: CIRPAS 95 GHz Frequency Modulated Continuous Wave (FMCW) Cloud Radar (Centroid Frequency Chirp Rate [CFCR]); operations overseen by Drs. Ghate and Albrecht. 3. Ceilometer: Vaisala CK-14; operations overseen by Drs. Ghate and Albrecht.« less

Kindergarten and Primary School Children's Everyday, Synthetic, and Scientific Concepts of Clouds and Rainfall

NASA Astrophysics Data System (ADS)

Malleus, Elina; Kikas, Eve; Marken, Tiivi

2017-06-01

The purpose of this research was to explore children's understandings of everyday, synthetic and scientific concepts to enable a description of how abstract, verbally taught material relates to previous experience-based knowledge and the consistency of understanding about cloud formation. This study examined the conceptual understandings of cloud formation and rain in kindergarten (age 5-7), second (age 8-9) and fourth (age 10-11) grade children, who were questioned on the basis of structured interview technique. In order to represent consistency in children's answers, three different types of clouds were introduced (a cirrus cloud, a cumulus cloud, and a rain cloud). Our results indicate that children in different age groups gave a similarly high amount of synthetic answers, which suggests the need for teachers to understand the formation process of different misconceptions to better support the learning process. Even children in kindergarten may have conceptions that represent different elements of scientific understanding and misconceptions cannot be considered age-specific. Synthetic understanding was also shown to be more consistent (not depending on cloud type) suggesting that gaining scientific understanding requires the reorganisation of existing concepts, that is time-consuming. Our results also show that the appearance of the cloud influences children's answers more in kindergarten where they mostly related rain cloud formation with water. An ability to create abstract connections between different concepts should also be supported at school as a part of learning new scientific information in order to better understand weather-related processes.

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/).

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

NASA Astrophysics Data System (ADS)

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

1999-09-01

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

Mash-up of techniques between data crawling/transfer, data preservation/stewardship and data processing/visualization technologies on a science cloud system designed for Earth and space science: a report of successful operation and science projects of the NICT Science Cloud

NASA Astrophysics Data System (ADS)

Murata, K. T.

2014-12-01

Data-intensive or data-centric science is 4th paradigm after observational and/or experimental science (1st paradigm), theoretical science (2nd paradigm) and numerical science (3rd paradigm). Science cloud is an infrastructure for 4th science methodology. The NICT science cloud is designed for big data sciences of Earth, space and other sciences based on modern informatics and information technologies [1]. Data flow on the cloud is through the following three techniques; (1) data crawling and transfer, (2) data preservation and stewardship, and (3) data processing and visualization. Original tools and applications of these techniques have been designed and implemented. We mash up these tools and applications on the NICT Science Cloud to build up customized systems for each project. In this paper, we discuss science data processing through these three steps. For big data science, data file deployment on a distributed storage system should be well designed in order to save storage cost and transfer time. We developed a high-bandwidth virtual remote storage system (HbVRS) and data crawling tool, NICTY/DLA and Wide-area Observation Network Monitoring (WONM) system, respectively. Data files are saved on the cloud storage system according to both data preservation policy and data processing plan. The storage system is developed via distributed file system middle-ware (Gfarm: GRID datafarm). It is effective since disaster recovery (DR) and parallel data processing are carried out simultaneously without moving these big data from storage to storage. Data files are managed on our Web application, WSDBank (World Science Data Bank). The big-data on the cloud are processed via Pwrake, which is a workflow tool with high-bandwidth of I/O. There are several visualization tools on the cloud; VirtualAurora for magnetosphere and ionosphere, VDVGE for google Earth, STICKER for urban environment data and STARStouch for multi-disciplinary data. There are 30 projects running on the NICT Science Cloud for Earth and space science. In 2003 56 refereed papers were published. At the end, we introduce a couple of successful results of Earth and space sciences using these three techniques carried out on the NICT Sciences Cloud. [1] http://sc-web.nict.go.jp

Radiative-dynamical and microphysical processes of thin cirrus clouds controlling humidity of air entering the stratosphere

NASA Astrophysics Data System (ADS)

Dinh, Tra; Fueglistaler, Stephan

2016-04-01

Thin cirrus clouds in the tropical tropopause layer (TTL) are of great interest due to their role in the control of water vapor and temperature in the TTL. Previous research on TTL cirrus clouds has focussed mainly on microphysical processes, specifically the ice nucleation mechanism and dehydration efficiency. Here, we use a cloud resolving model to analyse the sensitivity of TTL cirrus characteristics and impacts with respect to microphysical and radiative processes. A steady-state TTL cirrus cloud field is obtained in the model forced with dynamical conditions typical for the TTL (2-dimensional setup with a Kelvin-wave temperature perturbation). Our model results show that the dehydration efficiency (as given by the domain average relative humidity in the layer of cloud occurrence) is relatively insensitive to the ice nucleation mechanism, i.e. homogeneous versus heterogeneous nucleation. Rather, TTL cirrus affect the water vapor entering the stratosphere via an indirect effect associated with the cloud radiative heating and dynamics. Resolving the cloud radiative heating and the radiatively induced circulations approximately doubles the domain average ice mass. The cloud radiative heating is proportional to the domain average ice mass, and the observed increase in domain average ice mass induces a domain average temperature increase of a few Kelvin. The corresponding increase in water vapor entering the stratosphere is estimated to be about 30 to 40%.

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Future Suborbital Activities to Address Knowledge Gaps in Satellite and Model Assessments

NASA Technical Reports Server (NTRS)

Redemann, Jens; Wood, R.; Zuidema, P.; Haywood, J.; Piketh, S.; Formenti, P.; L'Ecuyer, T.; Kacenelenbogen, M.; Segal-Rosenheimer, M.; Shinozuka, Y.;

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Future Suborbital Activities to Address Knowledge Gaps in Satellite and Model Assessments

NASA Astrophysics Data System (ADS)

Redemann, J.; Wood, R.; Zuidema, P.; Haywood, J. M.; Piketh, S.; Formenti, P.; L'Ecuyer, T. S.; Kacenelenbogen, M. S.; Segal-Rosenhaimer, M.; Shinozuka, Y.; LeBlanc, S. E.; Vaughan, M. A.; Schmidt, S.; Flynn, C. J.; Song, S.; Schmid, B.; Luna, B.; Abel, S.

2015-12-01

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical stratocumulus (Sc) cloud decks in the world. The SE Atlantic stratocumulus deck interacts with the dense layers of BB aerosols that initially overlay the cloud deck, but later subside and may mix into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects, and their global representation in climate models remains one of the largest uncertainties in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for global climate change scenarios. Our understanding of aerosol-cloud interactions in the SE Atlantic is hindered both by the lack of knowledge on aerosol and cloud properties, as well as the lack of knowledge about detailed physical processes involved. Most notably, we are missing knowledge on the absorptive and cloud nucleating properties of aerosols, including their vertical distribution relative to clouds, on the locations and degree of aerosol mixing into clouds, on the processes that govern cloud property adjustments, and on the importance of aerosol effects on clouds relative to co-varying synoptic scale meteorology. We discuss the current knowledge of aerosol and cloud property distributions based on satellite observations and sparse suborbital sampling. Recent efforts to make full use of A-Train aerosol sensor synergies will be highlighted. We describe planned field campaigns in the region to address the existing knowledge gaps. Specifically, we describe the scientific objectives and implementation of the five synergistic, international research activities aimed at providing some of the key aerosol and cloud properties and a process-level understanding of aerosol-cloud interactions over the SE Atlantic: NASA's ORACLES, the UK Met Office's CLARIFY-2016, the DoE's LASIC, NSF's ONFIRE, and CNRS' AEROCLO-SA.

Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review.

PubMed

Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

2017-01-01

Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and high-resolution modeling on large domains are discussed.

Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

NASA Astrophysics Data System (ADS)

Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

2017-11-01

Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and high-resolution modeling on large domains are discussed.

Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

NASA Astrophysics Data System (ADS)

Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using observations and highresolution modeling on large domains are discussed.

Satellite view of the extreme haze clouds over China

NASA Astrophysics Data System (ADS)

Minghui, T.; Chen, L.; Wang, Z.

2013-12-01

Minghui Tao*, Liangfu Chen, Zifeng Wang State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China *Email: tmh1985@163.com ABSTRACT: In the past decades, great increases in anthropogenic emissions have caused dramatic changes in air quality and regional climate in China, which are further complicated by the natural processes such as dust events and atmospheric dynamics such as variations in intensity of the Asian monsoon. The common urban photochemistry smog, haze, and fog-haze pollution lead to poor air quality in major cities in eastern and middle parts of China. On the other hand, the heavy aerosol loading exerts marked influences on radiation, clouds, and precipitation over China. Satellites usually observed widespread haze clouds over eastern China. In most of previous studies, the dense haze clouds were directly connected with accumulation of anthropogenic emissions. However, satellite observations show that formation processes of haze clouds and local pollution near surface were different. Understanding the connections and interactions between haze clouds and local anthropogenic emissions is essential in chemistry and climate modeling of the aerosols over China. In January 2013, durative haze clouds covered most parts of eastern China, leading to extreme pollution events in many cities. With integrated A-train satellite observations and ground measurements, we investigated variations, optical properties, vertical structures as well as formation process of the extreme haze clouds over eastern China. Satellite-surface results were compared to analyze relations between the haze clouds and surface pollution. Different from traditional views, our results reveal that variation and formation of the haze clouds were driven by large-scale natural processes rather than local anthropogenic emissions. Figure 1. Aqua MODIS true color images of the haze clouds over eastern China on Jan 10, 2013.

Big Data, Internet of Things and Cloud Convergence--An Architecture for Secure E-Health Applications.

PubMed

Suciu, George; Suciu, Victor; Martian, Alexandru; Craciunescu, Razvan; Vulpe, Alexandru; Marcu, Ioana; Halunga, Simona; Fratu, Octavian

2015-11-01

Big data storage and processing are considered as one of the main applications for cloud computing systems. Furthermore, the development of the Internet of Things (IoT) paradigm has advanced the research on Machine to Machine (M2M) communications and enabled novel tele-monitoring architectures for E-Health applications. However, there is a need for converging current decentralized cloud systems, general software for processing big data and IoT systems. The purpose of this paper is to analyze existing components and methods of securely integrating big data processing with cloud M2M systems based on Remote Telemetry Units (RTUs) and to propose a converged E-Health architecture built on Exalead CloudView, a search based application. Finally, we discuss the main findings of the proposed implementation and future directions.

Identification of pixels with stray light and cloud shadow contaminations in the satellite ocean color data processing.

PubMed

Jiang, Lide; Wang, Menghua

2013-09-20

A new flag/masking scheme has been developed for identifying stray light and cloud shadow pixels that significantly impact the quality of satellite-derived ocean color products. Various case studies have been carried out to evaluate the performance of the new cloud contamination flag/masking scheme on ocean color products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). These include direct visual assessments, detailed quantitative case studies, objective statistic analyses, and global image examinations and comparisons. The National Oceanic and Atmospheric Administration (NOAA) Multisensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing system has been used in the study. The new stray light and cloud shadow identification method has been shown to outperform the current stray light flag in both valid data coverage and data quality of satellite-derived ocean color products. In addition, some cloud-related flags from the official VIIRS-SNPP data processing software, i.e., the Interface Data Processing System (IDPS), have been assessed. Although the data quality with the IDPS flags is comparable to that of the new flag implemented in the NOAA-MSL12 ocean color data processing system, the valid data coverage from the IDPS is significantly less than that from the NOAA-MSL12 using the new stray light and cloud shadow flag method. Thus, the IDPS flag/masking algorithms need to be refined and modified to reduce the pixel loss, e.g., the proposed new cloud contamination flag/masking can be implemented in IDPS VIIRS ocean color data processing.

Laboratory study of microphysical and scattering properties of corona-producing cirrus clouds.

PubMed

Järvinen, E; Vochezer, P; Möhler, O; Schnaiter, M

2014-11-01

Corona-producing cirrus clouds were generated and measured under chamber conditions at the AIDA cloud chamber in Karlsruhe. We were able to measure the scattering properties as well as microphysical properties of these clouds under well-defined laboratory conditions in contrast with previous studies of corona-producing clouds, where the measurements were conducted by means of lidar and in situ aircraft measurements. Our results are in agreement with those of previous studies, confirming that corona-producing cirrus clouds consist of a narrow distribution of small (median D_p=19-32  μm) and compact ice crystals. We showed that the ice crystals in these clouds are most likely formed in homogeneous freezing processes. As a result of the homogeneous freezing process, the ice crystals grow uniformly in size; furthermore, the majority of the ice crystals have rough surface features.

Microsecond-scale electric field pulses in cloud lightning discharges

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

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

NASA Astrophysics Data System (ADS)

Lamraoui, Fayçal; Roberts, Greg; Burnet, Frédéric

2016-04-01

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

A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models

NASA Astrophysics Data System (ADS)

Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.

2016-12-01

Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Processing Uav and LIDAR Point Clouds in Grass GIS

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Entrainment and cloud evaporation deduced from the stable isotope chemistry of clouds during ORACLES

NASA Astrophysics Data System (ADS)

Noone, D.; Henze, D.; Rainwater, B.; Toohey, D. W.

2017-12-01

The magnitude of the influence of biomass burning aerosols on cloud and rain processes is controlled by a series of processes which are difficult to measure directly. A consequence of this limitation is the emergence of significant uncertainty in the representation of cloud-aerosol interactions in models and the resulting cloud radiative forcing. Interaction between cloud and the regional atmosphere causes evaporation, and the rate of evaporation at cloud top is controlled in part by entrainment of air from above which exposes saturated cloud air to drier conditions. Similarly, the size of cloud droplets also controls evaporation rates, which in turn is linked to the abundance of condensation nuclei. To quantify the dependence of cloud properties on biomass burning aerosols the dynamic relationship between evaporation, drop size and entrainment on aerosol state, is evaluated for stratiform clouds in the southeast Atlantic Ocean. These clouds are seasonally exposed to biomass burning plumes from agricultural fires in southern Africa. Measurements of the stable isotope ratios of cloud water and total water are used to deduce the disequilibrium responsible for evaporation within clouds. Disequilibrium is identified by the relationship between hydrogen and oxygen isotope ratios of water vapor and cloud water in and near clouds. To obtain the needed information, a custom-built, dual inlet system was deployed alongside isotopic gas analyzers on the NASA Orion aircraft as part of the Observations of Aerosols above Clouds and their Interactions (ORACLES) campaign. The sampling system obtains both total water and cloud liquid content for the population of droplets above 7 micrometer diameter. The thermodynamic modeling required to convert the observed equilibrium and kinetic isotopic is linked to evaporation and entrainment is described, and the performance of the measurement system is discussed.

Cloud Modeling

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Insights into Aqueous-phase processing through Comparison of the Organic Chemical Composition of Atmospheric Particles and Cloud Water in the Southeast United States

NASA Astrophysics Data System (ADS)

Boone, E.; Laskin, J.; Laskin, A.; Wirth, C.; Shepson, P. B.; Stirm, B. H.; Pratt, K.

2014-12-01

Organic compounds comprise a significant mass fraction of submicron atmospheric particles with considerable contribution from secondary organic aerosol (SOA), a large fraction of which is formed from the oxidation of biogenic volatile organic compounds. Aqueous-phase reactions in particles and cloud droplets are suggested to increase SOA mass and change the chemical composition the particles following cloud evaporation. Aqueous-phase processing may also explain discrepancies between measurements and models. To gain a better understanding of these processes, cloud water and below-cloud atmospheric particles were collected onboard a research aircraft during the Southeast Oxidants and Aerosol Study (SOAS) over Alabama in June 2013. Nanospray desorption electrospray ionization (nano-DESI) and direct electrospray ionization (ESI) coupled with high resolution mass spectrometry were utilized to compare the organic molecular composition of the particle and cloud water samples, respectively. Several hundred unique compounds have been identified in the particle and cloud water samples, allowing possible aqueous-phase reactions to be examined. Hydrolysis of organosulfate compounds, aqueous-phase formation of nitrogen-containing compounds, and possible fragmentation of oligomeric compounds will be discussed, with comparisons to previous laboratory studies. This study provides insights into aqueous-phase reactions in ambient cloud droplets.

A Multi-Objective Compounded Local Mobile Cloud Architecture Using Priority Queues to Process Multiple Jobs.

PubMed

Wei, Xiaohui; Sun, Bingyi; Cui, Jiaxu; Xu, Gaochao

2016-01-01

As a result of the greatly increased use of mobile devices, the disadvantages of portable devices have gradually begun to emerge. To solve these problems, the use of mobile cloud computing assisted by cloud data centers has been proposed. However, cloud data centers are always very far from the mobile requesters. In this paper, we propose an improved multi-objective local mobile cloud model: Compounded Local Mobile Cloud Architecture with Dynamic Priority Queues (LMCpri). This new architecture could briefly store jobs that arrive simultaneously at the cloudlet in different priority positions according to the result of auction processing, and then execute partitioning tasks on capable helpers. In the Scheduling Module, NSGA-II is employed as the scheduling algorithm to shorten processing time and decrease requester cost relative to PSO and sequential scheduling. The simulation results show that the number of iteration times that is defined to 30 is the best choice of the system. In addition, comparing with LMCque, LMCpri is able to effectively accommodate a requester who would like his job to be executed in advance and shorten execution time. Finally, we make a comparing experiment between LMCpri and cloud assisting architecture, and the results reveal that LMCpri presents a better performance advantage than cloud assisting architecture.

A Multi-Objective Compounded Local Mobile Cloud Architecture Using Priority Queues to Process Multiple Jobs

PubMed Central

Wei, Xiaohui; Sun, Bingyi; Cui, Jiaxu; Xu, Gaochao

2016-01-01

As a result of the greatly increased use of mobile devices, the disadvantages of portable devices have gradually begun to emerge. To solve these problems, the use of mobile cloud computing assisted by cloud data centers has been proposed. However, cloud data centers are always very far from the mobile requesters. In this paper, we propose an improved multi-objective local mobile cloud model: Compounded Local Mobile Cloud Architecture with Dynamic Priority Queues (LMCpri). This new architecture could briefly store jobs that arrive simultaneously at the cloudlet in different priority positions according to the result of auction processing, and then execute partitioning tasks on capable helpers. In the Scheduling Module, NSGA-II is employed as the scheduling algorithm to shorten processing time and decrease requester cost relative to PSO and sequential scheduling. The simulation results show that the number of iteration times that is defined to 30 is the best choice of the system. In addition, comparing with LMCque, LMCpri is able to effectively accommodate a requester who would like his job to be executed in advance and shorten execution time. Finally, we make a comparing experiment between LMCpri and cloud assisting architecture, and the results reveal that LMCpri presents a better performance advantage than cloud assisting architecture. PMID:27419854

A methodology for cloud masking uncalibrated lidar signals

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; D'Amico, Giuseppe; Baars, Holger; Belegante, Livio; Marinou, Eleni

2018-04-01

Most lidar processing algorithms, such as those included in EARLINET's Single Calculus Chain, can be applied only to cloud-free atmospheric scenes. In this paper, we present a methodology for masking clouds in uncalibrated lidar signals. First, we construct a reference dataset based on manual inspection and then train a classifier to separate clouds and cloud-free regions. Here we present details of this approach together with an example cloud masks from an EARLINET station.

Extraction of convective cloud parameters from Doppler Weather Radar MAX(Z) product using Image Processing Technique

NASA Astrophysics Data System (ADS)

Arunachalam, M. S.; Puli, Anil; Anuradha, B.

2016-07-01

In the present work continuous extraction of convective cloud optical information and reflectivity (MAX(Z) in dBZ) using online retrieval technique for time series data production from Doppler Weather Radar (DWR) located at Indian Meteorological Department, Chennai has been developed in MATLAB. Reflectivity measurements for different locations within the DWR range of 250 Km radii of circular disc area can be retrieved using this technique. It gives both time series reflectivity of point location and also Range Time Intensity (RTI) maps of reflectivity for the corresponding location. The Graphical User Interface (GUI) developed for the cloud reflectivity is user friendly; it also provides the convective cloud optical information such as cloud base height (CBH), cloud top height (CTH) and cloud optical depth (COD). This technique is also applicable for retrieving other DWR products such as Plan Position Indicator (Z, in dBZ), Plan Position Indicator (Z, in dBZ)-Close Range, Volume Velocity Processing (V, in knots), Plan Position Indicator (V, in m/s), Surface Rainfall Intensity (SRI, mm/hr), Precipitation Accumulation (PAC) 24 hrs at 0300UTC. Keywords: Reflectivity, cloud top height, cloud base, cloud optical depth

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Modelling and intepreting the isotopic composition of water vapour in convective updrafts

NASA Astrophysics Data System (ADS)

Bolot, M.; Legras, B.; Moyer, E. J.

2012-08-01

The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener-Bergeron-Findeisen process). As all of these processes are related to updraft strength, droplet size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

Modelling and interpreting the isotopic composition of water vapour in convective updrafts

NASA Astrophysics Data System (ADS)

Bolot, M.; Legras, B.; Moyer, E. J.

2013-08-01

The isotopic compositions of water vapour and its condensates have long been used as tracers of the global hydrological cycle, but may also be useful for understanding processes within individual convective clouds. We review here the representation of processes that alter water isotopic compositions during processing of air in convective updrafts and present a unified model for water vapour isotopic evolution within undiluted deep convective cores, with a special focus on the out-of-equilibrium conditions of mixed-phase zones where metastable liquid water and ice coexist. We use our model to show that a combination of water isotopologue measurements can constrain critical convective parameters, including degree of supersaturation, supercooled water content and glaciation temperature. Important isotopic processes in updrafts include kinetic effects that are a consequence of diffusive growth or decay of cloud particles within a supersaturated or subsaturated environment; isotopic re-equilibration between vapour and supercooled droplets, which buffers isotopic distillation; and differing mechanisms of glaciation (droplet freezing vs. the Wegener-Bergeron-Findeisen process). As all of these processes are related to updraft strength, particle size distribution and the retention of supercooled water, isotopic measurements can serve as a probe of in-cloud conditions of importance to convective processes. We study the sensitivity of the profile of water vapour isotopic composition to differing model assumptions and show how measurements of isotopic composition at cloud base and cloud top alone may be sufficient to retrieve key cloud parameters.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Particle size distribution properties in mixed-phase monsoon clouds from in situ measurements during CAIPEEX

NASA Astrophysics Data System (ADS)

Patade, Sachin; Prabha, T. V.; Axisa, D.; Gayatri, K.; Heymsfield, A.

2015-10-01

A comprehensive analysis of particle size distributions measured in situ with airborne instrumentation during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) is presented. In situ airborne observations in the developing stage of continental convective clouds during premonsoon (PRE), transition, and monsoon (MON) period at temperatures from 25 to -22°C are used in the study. The PRE clouds have narrow drop size and particle size distributions compared to monsoon clouds and showed less development of size spectra with decrease in temperature. Overall, the PRE cases had much lower values of particle number concentrations and ice water content compared to MON cases, indicating large differences in the ice initiation and growth processes between these cloud regimes. This study provided compelling evidence that in addition to dynamics, aerosol and moisture are important for modulating ice microphysical processes in PRE and MON clouds through impacts on cloud drop size distribution. Significant differences are observed in the relationship of the slope and intercept parameters of the fitted particle size distributions (PSDs) with temperature in PRE and MON clouds. The intercept values are higher in MON clouds than PRE for exponential distribution which can be attributed to higher cloud particle number concentrations and ice water content in MON clouds. The PRE clouds tend to have larger values of dispersion of gamma size distributions than MON clouds, signifying narrower spectra. The relationships between PSDs parameters are presented and compared with previous observations.

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Decision-Making Processes of SME in Cloud Computing Adoption to Create Disruptive Innovation: Mediating Effect of Collaboration

ERIC Educational Resources Information Center

Sonthiprasat, Rattanawadee

2014-01-01

THE PROBLEM. The purpose of this quantitative correlation study was to assess the relationship between different Cloud service levels of effective business innovation for SMEs. In addition, the new knowledge gained from the benefits of Cloud adoption with knowledge sharing would enhance the decision making process for businesses to consider the…

Creation of a Unified Educational Space within a SLA University Classroom Using Cloud Storage and On-Line Applications

ERIC Educational Resources Information Center

Karabayeva, Kamilya Zhumartovna

2016-01-01

In the present article the author gives evidence of effective application of cloud storage and on-line applications in the educational process of the higher education institution, as well as considers the problems and prospects of using cloud technologies in the educational process, when creating a unified educational space in the foreign language…

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

NASA Technical Reports Server (NTRS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.;

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

DOE PAGES

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

2008-02-27

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

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

NASA Astrophysics Data System (ADS)

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

2008-02-01

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

New single-aircraft integrated atmospheric observation capabilities

NASA Astrophysics Data System (ADS)

Wang, Z.

2011-12-01

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

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Evaluating aerosol influence on cloud models using in-situ measurements during the INUPIAQ campaign

NASA Astrophysics Data System (ADS)

Farrington, R.; Connolly, P.; Choularton, T.; Bower, K.; Lloyd, G.; Flynn, M.; Crosier, J.; Field, P.

2014-12-01

At temperatures between -35°C and 0°C, the presence of insoluble aerosols acting as ice nuclei (IN) initiate the nucleation of ice under atmospheric conditions. Previous field and laboratory campaigns have suggested that mineral dust present in the atmosphere act as IN at temperatures around -20°C (e.g. Sassen et al. 2003), however the cause of ice nucleation at temperatures of around -5°C is less certain. Coupled with the limited representation of aerosol and cloud processes in large-scale weather and climate models, the need for improved in-situ measurements of aerosol properties and cloud micro-physical processes to drive the improvement of aerosol-clouds processes in models is evident. As part of the Ice NUcleation Process Investigation and Quantification (INUPIAQ) project, two field campaigns were conducted in early 2013 and early 2014. Both campaigns included measurements of cloud micro-physical properties at the summit of Jungfraujoch in Switzerland (3580m asl). Using data from the 2013 campaign and modelling simulations from the Weather Research and Forecasting model (WRF), an upwind site, located at Schilthorn (2970m asl), was determined for measuring aerosol properties out of cloud during the 2014 campaign. Further measurements of the cloud and aerosols properties were taken remotely using a doppler LiDAR located at Kleine Scheidegg (2061m asl). The aim of this project is to determine whether detailed aerosol information is important to determining cloud and precipitation properties downwind. To this end WRF was run using the aerosol number concentrations and size distributions measured at the Schilthorn site to compare modelled ice number concentrations with measurements taken at Jungfraujoch using state of the science cloud ice probes, including the Three-View Cloud Particle Imager (3V-CPI) and the Cloud Aerosol Spectrometer with Depolarization (CAS-DPOL), with the results of the comparison presented and discussed at this meeting. ReferencesSassen, K., et al, 2003: Saharan dust storms and indirect aerosol effects on clouds: Crystal-face results. Geophys. Res. Lett., 30(12), 1633-1636.

Cloud and Radiation Mission with Active and Passive Sensing from the Space Station

NASA Technical Reports Server (NTRS)

Spinhirne, James D.

1998-01-01

A cloud and aerosol radiative forcing and physical process study involving active laser and radar profiling with a combination of passive radiometric sounders and imagers would use the space station as an observation platform. The objectives are to observe the full three dimensional cloud and aerosol structure and the associated physical parameters leading to a complete measurement of radiation forcing processes. The instruments would include specialized radar and lidar for cloud and aerosol profiling, visible, infrared and microwave imaging radiometers with comprehensive channels for cloud and aerosol observation and specialized sounders. The low altitude,. available power and servicing capability of the space station are significant advantages for the active sensors and multiple passive instruments.

Study of the Evolution of the Electric Structure of a Convective Cloud Using the Data of a Numerical Nonstationary Three-Dimensional Model

NASA Astrophysics Data System (ADS)

Veremey, N. E.; Dovgalyuk, Yu. A.; Zatevakhin, M. A.; Ignatyev, A. A.; Morozov, V. N.

2014-04-01

Numerical nonstationary three-dimensional model of a convective cloud with parameterized description of microphysical processes with allowance for the electrization processes is considered. The results of numerical modeling of the cloud evolution for the specified atmospheric conditions are presented. The spatio-temporal distribution of the main cloud characteristics including the volume charge density and the electric field is obtained. The calculation results show that the electric structure of the cloud is different at its various life stages, i.e., it varies from unipolar to dipolar and then to tripolar. This conclusion is in fair agreement with the field studies.

Anvil Glaciation in a Deep Cumulus Updraught over Florida Simulated with the Explicit Microphysics Model. I: Impact of Various Nucleation Processes

NASA Technical Reports Server (NTRS)

Phillips, Vaughan T. J.; Andronache, Constantin; Sherwood, Steven C.; Bansemer, Aaron; Conant, William C.; Demott, Paul J.; Flagan, Richard C.; Heymsfield, Andy; Jonsson, Haflidi; Poellot, Micheal;

Usalpharma: A Cloud-Based Architecture to Support Quality Assurance Training Processes in Health Area Using Virtual Worlds

PubMed Central

García-Peñalvo, Francisco J.; Pérez-Blanco, Jonás Samuel; Martín-Suárez, Ana

2014-01-01

This paper discusses how cloud-based architectures can extend and enhance the functionality of the training environments based on virtual worlds and how, from this cloud perspective, we can provide support to analysis of training processes in the area of health, specifically in the field of training processes in quality assurance for pharmaceutical laboratories, presenting a tool for data retrieval and analysis that allows facing the knowledge discovery in the happenings inside the virtual worlds. PMID:24778593

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.

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.

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.

Combined observational and modeling efforts of aerosol-cloud-precipitation interactions over Southeast Asia

NASA Astrophysics Data System (ADS)

Loftus, Adrian; Tsay, Si-Chee; Nguyen, Xuan Anh

2016-04-01

Low-level stratocumulus (Sc) clouds cover more of the Earth's surface than any other cloud type rendering them critical for Earth's energy balance, primarily via reflection of solar radiation, as well as their role in the global hydrological cycle. Stratocumuli are particularly sensitive to changes in aerosol loading on both microphysical and macrophysical scales, yet the complex feedbacks involved in aerosol-cloud-precipitation interactions remain poorly understood. Moreover, research on these clouds has largely been confined to marine environments, with far fewer studies over land where major sources of anthropogenic aerosols exist. The aerosol burden over Southeast Asia (SEA) in boreal spring, attributed to biomass burning (BB), exhibits highly consistent spatiotemporal distribution patterns, with major variability due to changes in aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from source regions, the transported BB aerosols often overlap with low-level Sc cloud decks associated with the development of the region's pre-monsoon system, providing a unique, natural laboratory for further exploring their complex micro- and macro-scale relationships. Compared to other locations worldwide, studies of springtime biomass-burning aerosols and the predominately Sc cloud systems over SEA and their ensuing interactions are underrepresented in scientific literature. Measurements of aerosol and cloud properties, whether ground-based or from satellites, generally lack information on microphysical processes; thus cloud-resolving models are often employed to simulate the underlying physical processes in aerosol-cloud-precipitation interactions. The Goddard Cumulus Ensemble (GCE) cloud model has recently been enhanced with a triple-moment (3M) bulk microphysics scheme as well as the Regional Atmospheric Modeling System (RAMS) version 6 aerosol module. Because the aerosol burden not only affects cloud droplet size and number concentration, but also the spectral width of the cloud droplet size distribution, the 3M scheme is well suited to simulate aerosol-cloud-precipitation interactions within a three-dimensional regional cloud model. Moreover, the additional variability predicted on the hydrometeor distributions provides beneficial input for forward models to link the simulated microphysical processes with observations as well as to assess both ground-based and satellite retrieval methods. In this presentation, we provide an overview of the 7 South East Asian Studies / Biomass-burning Aerosols and Stratocumulus Environment: Lifecycles and Interactions Experiment (7-SEAS/BASELInE) operations during the spring of 2013. Preliminary analyses of pre-monsoon Sc system lifecycles observed during the first-ever deployment of a ground-based cloud radar to northern Vietnam will be also be presented. Initial results from GCE model simulations of these Sc using double-moment and the new 3M bulk microphysics schemes under various aerosol loadings will be used to showcase the 3M scheme as well as provide insight into how the impact of aerosols on cloud and precipitation processes in stratocumulus over land may manifest themselves in simulated remote-sensing signals. Applications and future work involving ongoing 7-SEAS campaigns aimed at improving our understanding of aerosol-cloud-precipitation interactions of will also be discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Cloud screening Coastal Zone Color Scanner images using channel 5

NASA Technical Reports Server (NTRS)

Eckstein, B. A.; Simpson, J. J.

1991-01-01

Clouds are removed from Coastal Zone Color Scanner (CZCS) data using channel 5. Instrumentation problems require pre-processing of channel 5 before an intelligent cloud-screening algorithm can be used. For example, at intervals of about 16 lines, the sensor records anomalously low radiances. Moreover, the calibration equation yields negative radiances when the sensor records zero counts, and pixels corrupted by electronic overshoot must also be excluded. The remaining pixels may then be used in conjunction with the procedure of Simpson and Humphrey to determine the CZCS cloud mask. These results plus in situ observations of phytoplankton pigment concentration show that pre-processing and proper cloud-screening of CZCS data are necessary for accurate satellite-derived pigment concentrations. This is especially true in the coastal margins, where pigment content is high and image distortion associated with electronic overshoot is also present. The pre-processing algorithm is critical to obtaining accurate global estimates of pigment from spacecraft data.

Boundary Conditions for the Paleoenvironment: Chemical and Physical Processes in the Pre-Solar Nebula

NASA Technical Reports Server (NTRS)

Irvine, William M.; Schloerb, F. Peter

1997-01-01

The basic theme of this program is the study of molecular complexity and evolution in interstellar clouds and in primitive solar system objects. Research has included the detection and study of a number of new interstellar molecules and investigation of reaction pathways for astrochemistry from a comparison of theory and observed molecular abundances. The latter includes studies of cold, dark clouds in which ion-molecule chemistry should predominate, searches for the effects of interchange of material between the gas and solid phases in interstellar clouds, unbiased spectral surveys of particular sources, and systematic investigation of the interlinked chemistry and physics of dense interstellar clouds. In addition, the study of comets has allowed a comparison between the chemistry of such minimally thermally processed objects and that of interstellar clouds, shedding light on the evolution of the biogenic elements during the process of solar system formation.

Indian Summer Monsoon Drought 2009: Role of Aerosol and Cloud Microphysics

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

Hazra, Anupam; Taraphdar, Sourav; Halder, Madhuparna

2013-07-01

Cloud dynamics played a fundamental role in defining Indian summer monsoon (ISM) rainfall during drought in 2009. The anomalously negative precipitation was consistent with cloud properties. Although, aerosols inhibited the growth of cloud effective radius in the background of sparse water vapor, their role is secondary. The primary role, however, is played by the interactive feedback between cloud microphysics and dynamics owing to reduced efficient cloud droplet growth, lesser latent heating release and shortage of water content. Cloud microphysical processes were instrumental for the occurrence of ISM drought 2009.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

Fog and Cloud Induced Aerosol Modification Observed by AERONET

NASA Technical Reports Server (NTRS)

Eck, T. F.; Holben, B. N.; Reid, J. S.; Giles, D. M.; Rivas, M. A.; Singh, R. P.; Tripathi, S. N.; Bruegge, C. J.; Platnick, S. E.; Arnold, G. T.;

Effects of environment forcing on marine boundary layer cloud-drizzle processes: MBL Cloud-Drizzle Processes

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

Wu, Peng; Dong, Xiquan; Xi, Baike

Determining the factors affecting drizzle formation in marine boundary layer (MBL) clouds remains a challenge for both observation and modeling communities. To investigate the roles of vertical wind shear and buoyancy (static instability) in drizzle formation, ground-based observations from the Atmospheric Radiation Measurement (ARM) Program at the Azores are analyzed for two types of conditions. The type I clouds should last for at least five hours and more than 90% time must be non-drizzling, and then followed by at least two hours of drizzling periods while the type II clouds are characterized by mesoscale convection cellular (MCC) structures with drizzlemore » occur every two to four hours. By analyzing the boundary layer wind profiles (direction and speed), it was found that either directional or speed shear is required to promote drizzle production in the type I clouds. Observations and a recent model study both suggest that vertical wind shear helps the production of turbulent kinetic energy (TKE), stimulates turbulence within cloud layer, and enhances drizzle formation near the cloud top. The type II clouds do not require strong wind shear to produce drizzle. The small values of lower-tropospheric stability (LTS) and negative Richardson number ( Ri) in the type II cases suggest that boundary layer instability plays an important role in TKE production and cloud-drizzle processes. As a result, by analyzing the relationships between LTS and wind shear for all cases and all time periods, a stronger connection was found between LTS and wind directional shear than that between LTS and wind speed shear.« less

Effects of environment forcing on marine boundary layer cloud-drizzle processes: MBL Cloud-Drizzle Processes

DOE PAGES

Wu, Peng; Dong, Xiquan; Xi, Baike; ...

2017-04-20

Determining the factors affecting drizzle formation in marine boundary layer (MBL) clouds remains a challenge for both observation and modeling communities. To investigate the roles of vertical wind shear and buoyancy (static instability) in drizzle formation, ground-based observations from the Atmospheric Radiation Measurement (ARM) Program at the Azores are analyzed for two types of conditions. The type I clouds should last for at least five hours and more than 90% time must be non-drizzling, and then followed by at least two hours of drizzling periods while the type II clouds are characterized by mesoscale convection cellular (MCC) structures with drizzlemore » occur every two to four hours. By analyzing the boundary layer wind profiles (direction and speed), it was found that either directional or speed shear is required to promote drizzle production in the type I clouds. Observations and a recent model study both suggest that vertical wind shear helps the production of turbulent kinetic energy (TKE), stimulates turbulence within cloud layer, and enhances drizzle formation near the cloud top. The type II clouds do not require strong wind shear to produce drizzle. The small values of lower-tropospheric stability (LTS) and negative Richardson number ( Ri) in the type II cases suggest that boundary layer instability plays an important role in TKE production and cloud-drizzle processes. As a result, by analyzing the relationships between LTS and wind shear for all cases and all time periods, a stronger connection was found between LTS and wind directional shear than that between LTS and wind speed shear.« less

SeReNA Project: studying aerosol interactions with cloud microphysics in the Amazon Basin

NASA Astrophysics Data System (ADS)

Correia, A. L.; Catandi, P. B.; Frigeri, F. F.; Ferreira, W. C.; Martins, J.; Artaxo, P.

2012-12-01

Cloud microphysics and its interaction with aerosols is a key atmospheric process for weather and climate. Interactions between clouds and aerosols can impact Earth's radiative balance, its hydrological and energetic cycles, and are responsible for a large fraction of the uncertainty in climatic models. On a planetary scale, the Amazon Basin is one of the most significant land sources of moisture and latent heat energy. Moreover, every year this region undergoes mearked seasonal shifts in its atmospheric state, transitioning from clean to heavily polluted conditions due to the occurrence of seasonal biomass burning fires, that emit large amounts of smoke to the atmosphere. These conditions make the Amazon Basin a special place to study aerosol-cloud interactions. The SeReNA Project ("Remote sensing of clouds and their interaction with aerosols", from the acronym in Portuguese, @SerenaProject on Twitter) is an ongoing effort to experimentally investigate the impact of aerosols upon cloud microphysics in Amazonia. Vertical profiles of droplet effective radius of water and ice particles, in single convective clouds, can be derived from measurements of the emerging radiation on cloud sides. Aerosol optical depth, cloud top properties, and meteorological parameters retrieved from satellites will be correlated with microphysical properties derived for single clouds. Maps of cloud brightness temperature will allow building temperature vs. effective radius profiles for hydrometeors in single clouds. Figure 1 shows an example extracted from Martins et al. (2011), illustrating a proof-of-concept for the kind of result expected within the framework for the SeReNA Project. The results to be obtained will help foster the quantitative knowledge about interactions between aerosols and clouds in a microphysical level. These interactions are a fundamental process in the context of global climatic changes, they are key to understanding basic processes within clouds and how aerosols can influence them. Reference: Martins et al. (2011) ACP, v.11, p.9485-9501. Available at: http://bit.ly/martinspaper Figure 1. Brightness temperature (left panel) and thermodynamic phase (right) of hydrometeors in the convective cloud shown in the middle panel. Extracted from Martins et al. (2011).

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

NASA Technical Reports Server (NTRS)

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

Tropical cloud buoyancy is the same in a world with or without ice

NASA Astrophysics Data System (ADS)

Seeley, Jacob T.; Romps, David M.

2016-04-01

When convective clouds grow above the melting line, where temperatures fall below 0°C, condensed water begins to freeze and water vapor is deposited. These processes release the latent heat of fusion, which warms cloud air, and many previous studies have suggested that this heating from fusion increases cloud buoyancy in the upper troposphere. Here we use numerical simulations of radiative-convective equilibrium with and without ice processes to argue that tropical cloud buoyancy is not systematically higher in a world with fusion than in a world without it. This insensitivity results from the fact that the environmental temperature profile encountered by developing tropical clouds is itself determined by convection. We also offer a simple explanation for the large reservoir of convective available potential energy in the tropical upper troposphere that does not invoke ice.

GATECloud.net: a platform for large-scale, open-source text processing on the cloud.

PubMed

Tablan, Valentin; Roberts, Ian; Cunningham, Hamish; Bontcheva, Kalina

2013-01-28

Cloud computing is increasingly being regarded as a key enabler of the 'democratization of science', because on-demand, highly scalable cloud computing facilities enable researchers anywhere to carry out data-intensive experiments. In the context of natural language processing (NLP), algorithms tend to be complex, which makes their parallelization and deployment on cloud platforms a non-trivial task. This study presents a new, unique, cloud-based platform for large-scale NLP research--GATECloud. net. It enables researchers to carry out data-intensive NLP experiments by harnessing the vast, on-demand compute power of the Amazon cloud. Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security and fault tolerance. We also include a cost-benefit analysis and usage evaluation.

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE PAGES

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...

2017-01-01

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

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

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

Next Generation Cloud-based Science Data Systems and Their Implications on Data and Software Stewardship, Preservation, and Provenance

NASA Astrophysics Data System (ADS)

Hua, H.; Manipon, G.; Starch, M.

2017-12-01

NASA's upcoming missions are expected to be generating data volumes at least an order of magnitude larger than current missions. A significant increase in data processing, data rates, data volumes, and long-term data archive capabilities are needed. Consequently, new challenges are emerging that impact traditional data and software management approaches. At large-scales, next generation science data systems are exploring the move onto cloud computing paradigms to support these increased needs. New implications such as costs, data movement, collocation of data systems & archives, and moving processing closer to the data, may result in changes to the stewardship, preservation, and provenance of science data and software. With more science data systems being on-boarding onto cloud computing facilities, we can expect more Earth science data records to be both generated and kept in the cloud. But at large scales, the cost of processing and storing global data may impact architectural and system designs. Data systems will trade the cost of keeping data in the cloud with the data life-cycle approaches of moving "colder" data back to traditional on-premise facilities. How will this impact data citation and processing software stewardship? What are the impacts of cloud-based on-demand processing and its affect on reproducibility and provenance. Similarly, with more science processing software being moved onto cloud, virtual machines, and container based approaches, more opportunities arise for improved stewardship and preservation. But will the science community trust data reprocessed years or decades later? We will also explore emerging questions of the stewardship of the science data system software that is generating the science data records both during and after the life of mission.

Microphysical Processes Affecting the Pinatubo Volcanic Plume

NASA Technical Reports Server (NTRS)

Hamill, Patrick; Houben, Howard; Young, Richard; Turco, Richard; Zhao, Jingxia

1996-01-01

In this paper we consider microphysical processes which affect the formation of sulfate particles and their size distribution in a dispersing cloud. A model for the dispersion of the Mt. Pinatubo volcanic cloud is described. We then consider a single point in the dispersing cloud and study the effects of nucleation, condensation and coagulation on the time evolution of the particle size distribution at that point.

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.

Cirrus cloud retrieval from MSG/SEVIRI during day and night using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca

2017-04-01

By covering a large part of the Earth, cirrus clouds play an important role in climate as they reflect incoming solar radiation and absorb outgoing thermal radiation. Nevertheless, the cirrus clouds remain one of the largest uncertainties in atmospheric research and the understanding of the physical processes that govern their life cycle is still poorly understood, as is their representation in climate models. To monitor and better understand the properties and physical processes of cirrus clouds, it's essential that those tenuous clouds can be observed from geostationary spaceborne imagers like SEVIRI (Spinning Enhanced Visible and InfraRed Imager), that possess a high temporal resolution together with a large field of view and play an important role besides in-situ observations for the investigation of cirrus cloud processes. CiPS (Cirrus Properties from Seviri) is a new algorithm targeting thin cirrus clouds. CiPS is an artificial neural network trained with coincident SEVIRI and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations in order to retrieve a cirrus cloud mask along with the cloud top height (CTH), ice optical thickness (IOT) and ice water path (IWP) from SEVIRI. By utilizing only the thermal/IR channels of SEVIRI, CiPS can be used during day and night making it a powerful tool for the cirrus life cycle analysis. Despite the great challenge of detecting thin cirrus clouds and retrieving their properties from a geostationary imager using only the thermal/IR wavelengths, CiPS performs well. Among the cirrus clouds detected by CALIOP, CiPS detects 70 and 95 % of the clouds with an optical thickness of 0.1 and 1.0 respectively. Among the cirrus free pixels, CiPS classify 96 % correctly. For the CTH retrieval, CiPS has a mean absolute percentage error of 10 % or less with respect to CALIOP for cirrus clouds with a CTH greater than 8 km. For the IOT retrieval, CiPS has a mean absolute percentage error of 100 % or less with respect to CALIOP for cirrus clouds with an optical thickness down to 0.07. For such thin cirrus clouds an error of 100 % should be regarded as low from a geostationary imager like SEVIRI. The IWP retrieved by CiPS shows a similar performance, but has larger deviations for the thinner cirrus clouds.

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2006-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CFWs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1 998 and 1999). In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Heterogeneous ice nucleation of α-pinene SOA particles before and after ice cloud processing

NASA Astrophysics Data System (ADS)

Wagner, Robert; Höhler, Kristina; Huang, Wei; Kiselev, Alexei; Möhler, Ottmar; Mohr, Claudia; Pajunoja, Aki; Saathoff, Harald; Schiebel, Thea; Shen, Xiaoli; Virtanen, Annele

2017-05-01

The ice nucleation ability of α-pinene secondary organic aerosol (SOA) particles was investigated at temperatures between 253 and 205 K in the Aerosol Interaction and Dynamics in the Atmosphere cloud simulation chamber. Pristine SOA particles were nucleated and grown from pure gas precursors and then subjected to repeated expansion cooling cycles to compare their intrinsic ice nucleation ability during the first nucleation event with that observed after ice cloud processing. The unprocessed α-pinene SOA particles were found to be inefficient ice-nucleating particles at cirrus temperatures, with nucleation onsets (for an activated fraction of 0.1%) as high as for the homogeneous freezing of aqueous solution droplets. Ice cloud processing at temperatures below 235 K only marginally improved the particles' ice nucleation ability and did not significantly alter their morphology. In contrast, the particles' morphology and ice nucleation ability was substantially modified upon ice cloud processing in a simulated convective cloud system, where the α-pinene SOA particles were first activated to supercooled cloud droplets and then froze homogeneously at about 235 K. As evidenced by electron microscopy, the α-pinene SOA particles adopted a highly porous morphology during such a freeze-drying cycle. When probing the freeze-dried particles in succeeding expansion cooling runs in the mixed-phase cloud regime up to 253 K, the increase in relative humidity led to a collapse of the porous structure. Heterogeneous ice formation was observed after the droplet activation of the collapsed, freeze-dried SOA particles, presumably caused by ice remnants in the highly viscous material or the larger surface area of the particles.

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment.

PubMed

Oh, Jeongsu; Choi, Chi-Hwan; Park, Min-Kyu; Kim, Byung Kwon; Hwang, Kyuin; Lee, Sang-Heon; Hong, Soon Gyu; Nasir, Arshan; Cho, Wan-Sup; Kim, Kyung Mo

2016-01-01

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology-a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr.

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment

PubMed Central

Park, Min-Kyu; Kim, Byung Kwon; Hwang, Kyuin; Lee, Sang-Heon; Hong, Soon Gyu; Nasir, Arshan; Cho, Wan-Sup; Kim, Kyung Mo

2016-01-01

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology–a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr. PMID:26954507

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

NASA Astrophysics Data System (ADS)

Lague, D.

2014-12-01

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

Algorithm for Automated Detection of Edges of Clouds

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.

2006-01-01

An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

Examination of turbulent entrainment-mixing mechanisms using a combined approach

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

Lu, C.; Liu, Y.; Niu, S.

2011-10-01

Turbulent entrainment-mixing mechanisms are investigated by applying a combined approach to the aircraft measurements of three drizzling and two nondrizzling stratocumulus clouds collected over the U.S. Department of Energy's Atmospheric Radiation Measurement Southern Great Plains site during the March 2000 cloud Intensive Observation Period. Microphysical analysis shows that the inhomogeneous entrainment-mixing process occurs much more frequently than the homogeneous counterpart, and most cases of the inhomogeneous entrainment-mixing process are close to the extreme scenario, having drastically varying cloud droplet concentration but roughly constant volume-mean radius. It is also found that the inhomogeneous entrainment-mixing process can occur both near the cloudmore » top and in the middle level of a cloud, and in both the nondrizzling clouds and nondrizzling legs in the drizzling clouds. A new dimensionless number, the scale number, is introduced as a dynamical measure for different entrainment-mixing processes, with a larger scale number corresponding to a higher degree of homogeneous entrainment mixing. Further empirical analysis shows that the scale number that separates the homogeneous from the inhomogeneous entrainment-mixing process is around 50, and most legs have smaller scale numbers. Thermodynamic analysis shows that sampling average of filament structures finer than the instrumental spatial resolution also contributes to the dominance of inhomogeneous entrainment-mixing mechanism. The combined microphysical-dynamical-thermodynamic analysis sheds new light on developing parameterization of entrainment-mixing processes and their microphysical and radiative effects in large-scale models.« less

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.

Evaluating stratiform cloud base charge remotely

NASA Astrophysics Data System (ADS)

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

2017-06-01

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