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Sample records for mase-marine stratus experiment-pt

  1. ARM - Field Campaign - 2005 MASE-MArine Stratus Experiment-Pt...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : 2005 MASE-MArine Stratus Experiment-Pt. Reyes, CA 2005.07.05 - 2005.07.27 Lead...

  2. ARM - Field Campaign - MASRAD: Pt. Reyes Stratus Cloud and Drizzle...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsMASRAD: Pt. Reyes Stratus Cloud and Drizzle Study Campaign Links AMF Point Reyes Website ARM Data Discovery Browse Data Related Campaigns MArine Stratus Radiation...

  3. ARM - Field Campaign - MArine Stratus Radiation Aerosol and Drizzle...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsMArine Stratus Radiation Aerosol and Drizzle (MASRAD) IOP Campaign Links Science Plan AMF Point Reyes Website AMF Point Reyes Data Plots ARM Data Discovery Browse Data...

  4. Arctic Stratus and Tropical Deep Convection. Integrating Measurements and

    Office of Scientific and Technical Information (OSTI)

    Simulations (Technical Report) | SciTech Connect Technical Report: Arctic Stratus and Tropical Deep Convection. Integrating Measurements and Simulations Citation Details In-Document Search Title: Arctic Stratus and Tropical Deep Convection. Integrating Measurements and Simulations Final report summarizing published material. Authors: Ann, Fridlind [1] + Show Author Affiliations NASA Goddard Institute for Space Studies, Washington, DC (United States) Publication Date: 2015-05-18 OSTI

  5. sgp_stratus_poster_v1.0.ppt

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Structure and Persistence of Post-frontal Stratus in Numerical Models D. B. Mechem 1 and Y. L. Kogan 2 1 Department of Geography, University of Kansas, 2 CIMMS, The University of Oklahoma Mid-latitude synoptic systems are frequently accompanied by broad areas of low-altitude cloudiness located behind the cold front. Field and Wood (J. Clim. 2007) show that these clouds constitute a significant climatological signal. How different are postfrontal continental stratus from marine stratocumulus?

  6. Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    and Relationship to Adiabacity Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences and Relationship to Adiabacity Kim, Byung-Gon Kangnung National University Schwartz, Stephen Brookhaven National Laboratory Miller, Mark Brookhaven National Laboratory Min, Qilong State University of New York at Albany Category: Cloud Properties The microphysical properties of continental stratus clouds observed over SGP appear to be substantially influenced by micrometeorological

  7. A Potential Role for Immersion Freezing in Arctic Mixed-Phase Stratus

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Potential Role for Immersion Freezing in Arctic Mixed-Phase Stratus Gijs de Boer, Edwin W. Eloranta, Tempei Hashino, and Gregory J. Tripoli The University of Wisconsin - Madison (1) Introduction Ice formation appears to a dominant factor controlling the lifecycle of Arctic mixed-phase clouds. To date, our understanding of ice formation in these long-lasting cloud structures does not explain the formation of observed ice amounts. Particularly puzzling are observa- tions taken from the 2004

  8. Equations Governing Space-Time Variability of Liquid Water Path in Stratus Clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Equations Governing Space-Time Variability of Liquid Water Path in Stratus Clouds K. Ivanova Pennsylvania State University University Park, Pennsylvania T. P. Ackerman Pacific Northwest National Laboratory Richland, Washington M. Ausloos University of Liège B-4000 Liège, Belgium Abstract We present a method on how to derive an underlying mathematical (statistical or model free) equation for a liquid water path (LWP) signal directly from empirical data. The evolution of the probability density

  9. Atmospheric Radiation Measurement (ARM) Data from Point Reyes, California for the Marine Stratus, Radiation, Aerosol, and Drizzle (MASRAD) Project

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Point Reyes National Seashore, on the California coast north of San Francisco, was the location of the first deployment of the DOE's Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The ARM Program collaborated with the U.S. Office of Naval Research and DOE's Aerosol Science Program in the Marine Stratus, Radiation, Aerosol, and Drizzle (MASRAD) project. Their objectives were to collect data from cloud/aerosol interactions and to improve understanding of cloud organization that is often associated with patches of drizzle. Between March and September 2005, the AMF and at least two research aircraft were used to collect data.

  10. Stratus Cloud Drizzle Retrieval During SHEBA from MMCR Doppler Moments

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Drizzle Retrieval During SHEBA from MMCR Doppler Moments A. S. Frisch National Oceanic and Atmospheric Administration Environmental Technology Laboratory Colorado State University Boulder, Colorado M. D. Shupe Science Technology Corporation National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado Introduction The National Oceanic and Atmospheric Administration/Environmental Technology Laboratory (NOAA/ETL) operated a 35-GHz cloud radar during the

  11. Stratus Cloud Structure from MM-Radar Transects and Satellite...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    modeling: * cloud-radiation interaction where correlations can trigger three-dimensional (3D) radiative transfer effects; and * dynamical cloud modeling where the goal is to...

  12. Arctic Stratus and Tropical Deep Convection. Integrating Measurements...

    Office of Scientific and Technical Information (OSTI)

    Have feedback or suggestions for a way to improve these results? Save Share this Record Citation Formats MLA APA Chicago Bibtex Export Metadata Endnote Excel CSV XML Save to My ...

  13. Analysis of Aerosol Indirect Effects in California Coastal Stratus...

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    Andrew Brookhaven National Laboratory Andrews, Betsy NOAACMDL Ogren, John NOAACMDL Turner, David University of Wisconsin-Madison Category: Field Campaigns Impacts of aerosol...

  14. gottschalck(2)-99.PDF

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Mesoscale Variability of a Continental Stratus Cloud Event at the SGP CART Site During 1999 J. C. Gottschalck and B. A. Albrecht University of Miami Miami, Florida Introduction Current observational data bases of continental stratus are mainly composed of observations from a single location. It has been shown, however, that marine stratus decks show both mesoscale and diurnal variability (Albrecht et al. 1988; Albrecht et al. 1995; Miller and Albrecht 1995; Miller et al. 1998). Such variability

  15. Microsoft PowerPoint - 13_hudarmoral.ppt [Compatibility Mode]

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    CCN Contrasts Below and Above CCN Contrasts Below and Above California Stratus California Stratus James G. Hudson Desert Research Institute Reno, Nevada 89512-1095 hudson@dri.edu The major features of the Desert Research Institute (DRI) j ( ) cloud condensation nuclei (CCN) measurements during the Marine Stratus Experiment (MASE) was 1) the vertical variability of the concentrations higher above than below cloud. 2) the consistently high concentrations that were uncharacteristic of the marine

  16. Research Highlight

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    nimbostratus (Nb), cumulus (Cu), stratocumulus (Sc) and stratus (St). Land masses are grey. Thick black contours denote identified MCSs. Progress in the representation of...

  17. Section 42

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    Cloud-Resolving Simulations of Arctic Stratus J. Y. Harrington, W. R. Cotton, S. Kreidenweis and P. Q. Olsson Department of Atmospheric Science Colorado State University Ft....

  18. Section 77

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    of cloud and boundary layer properties associated with continental stratus. But blind application of these statistics may not be the most prudent approach for the...

  19. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Mesoscale Model Investigations of the Lifecycles of Arctic Mixed-Phase Stratus Avramov, A., Harrington, J.Y., Verlinde, J., and Clothiaux, E.E., The Pennsylvania State...

  20. 1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    over both the land and ocean. Therefore, it is necessary that adequate observational databases exist for both continental and maritime boundary layer clouds. Stratus cloud and...

  1. ARM - Measurement - Cloud phase

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    that involves property descriptors such as stratus, cumulus, and cirrus. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  2. ARM - Measurement - Cloud type

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Measurement : Cloud type Cloud type such as cirrus, stratus, cumulus etc Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  3. ARM - Publications: Science Team Meeting Documents: The First...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The First Deployment of the ARM Mobile Facility; Investigating Marine Stratus at Pt. Reyes, CA Bartholomew, Mary Jane Brookhaven National Laboratory Miller, Mark Brookhaven...

  4. Microsoft PowerPoint - ARM08_hguo_080229.ppt

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Dynamics (U,V,W,T,Q,P,...) Radiation Microphysics Surface Turbulence * near Point Reyes, CA * on 19 July, 2005, a stratus deck over Pacific Ocean * comprehensive airborne...

  5. ARM - Campaign Instrument - qcsfcrad

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    MArine Stratus Radiation Aerosol and Drizzle (MASRAD) IOP Download Data Point Reyes CA, USA; Mobile Facility, 2005.03.14 - 2005.09.14 Primary Measurements Taken The...

  6. ARM - Field Campaign - MASRAD: Cloud Condensate Nuclei Chemistry...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Cloud Condensate Nuclei Chemistry Measurements Campaign Links AMF Point Reyes Website ARM Data Discovery Browse Data Related Campaigns MArine Stratus Radiation Aerosol and Drizzle...

  7. ARM - Field Campaign - MASRAD - Aerosol Optical Properties

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsMASRAD - Aerosol Optical Properties Campaign Links AMF Point Reyes Website ARM Data Discovery Browse Data Related Campaigns MArine Stratus Radiation Aerosol and Drizzle...

  8. Research Highlight

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Arctic stratus clouds: Sensitivity to ice initiation mechanisms." Atmospheric Chemistry and Physics Discussion 8: 11755-11819. The vertical structure and radiative...

  9. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Radiative Parameters of Stratus Clouds in ARESE II Austin, R.T. (a), Davis, J.M. (a), Miller, S.D. (b), and Stephens, G.L. (a), Colorado State University, Fort Collins (a), Naval...

  10. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Variability of Low Stratus Over the ARM SGP CART Based on Cloud Radar Data and LES Simulations Kogan, Z.N., Mechem, D.B., and Kogan, Y.L., Cooperative Institute for Mesoscale...

  11. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Relative Importance of Size Distribution and Liquid Water Path to Solar Radiation in the Presence of Continental Stratus Sengupta, M.(a), Ackerman, T.P.(a), and Clothiaux, E.E.(b),...

  12. ARM - Campaign Instrument - mmcr94miami

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    MArine Stratus Radiation Aerosol and Drizzle (MASRAD) IOP Download Data Point Reyes CA, USA; Mobile Facility, 2005.03.14 - 2005.09.14 Spring Cloud IOP Download Data ...

  13. ARM - Campaign Instrument - swfluxanal

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    MArine Stratus Radiation Aerosol and Drizzle (MASRAD) IOP Download Data Point Reyes CA, USA; Mobile Facility, 2005.03.14 - 2005.09.14 Mixed-Phase Arctic Cloud Experiment...

  14. ARM - Field Campaign - MASRAD: Cloud Study from the 2NFOV at...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsMASRAD: Cloud Study from the 2NFOV at Pt. Reyes Field Campaign Campaign Links AMF Point Reyes Website ARM Data Discovery Browse Data Related Campaigns MArine Stratus...

  15. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Comparison of Stratus Cloud Optical Depths Retrieved from Surface and GOES Measurements over the SGP ARM Central Facility Dong, X., and Smith, W.L. Jr., Analytical Services and...

  16. Macquarie Island Cloud and Radiation Experiment (MICRE) Science...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... doi:10.10292009JD013121. Dong, X and GG Mace. 2003. "Profiles of low-level stratus ... Geophysical Research Letters 34(22): L22710, doi:10.10292007GL031383. Mace, GG. 2010. ...

  17. 1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... Journal of Geophysical Research 107 (D23), 10.10292000JD000240. Dong, X, P Minnis, GG Mace, WL Smith, Jr., M Poellot, RT Marchand, and AD Rapp. 2002. Comparison of stratus cloud ...

  18. DOE/SC-ARM-10-021 STORMVEX: The Storm Peak Lab Cloud Property...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... 463, doi:10.1175JTECH1975.1. Dong, X, and GG Mace. 2003. "Profiles of low-level stratus ... Journal of Geophysical Research 107(D18): 4345, doi:10.10292001JD002046. Mace, GG, S ...

  19. Bench-Scale Cross Flow Filtration of

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... Boundary-Layer Meteorology 89: 75-107. Dong, X, and GG Mace. 2003. "Arctic stratus cloud properties and radiative forcing derived from ground-based data collected near Point ...

  20. frisch-98.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    9 On Stratus Cloud Liquid Water Profiles from a Cloud Radar and Microwave Radiometer A. S. Frisch and G. Feingold Cooperative Institute for Research in the Atmosphere Colorado State University and NOAA-Environmental Technology Laboratory Boulder, Colorado C. W. Fairall NOAA-Environmental Technology Laboratory Boulder, Colorado J. B. Snider Cooperative Institute for Research in the Atmosphere Colorado State University Boulder, Colorado Introduction Stratus clouds are important in boundary-layer

  1. Radiative Influences on Glaciation Time-Scales of Mixed-Phase Clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Radiative Influences on Glaciation Time-Scales of Mixed-Phase Clouds Harrington, Jerry The Pennsylvania State University Category: Modeling Mixed-phase stratus clouds are dominant in the Arctic during much of the year. These clouds typically have liquid tops that precipitate ice. Time scales for the complete glaciation of such clouds (the Bergeron process) are typically computed using the classical mass growth equations for crystals and liquid drops. However, mixed phase arctic stratus have

  2. ARM - Publications: Science Team Meeting Documents: Atmospheric Modes of

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Drizzling Stratus at the ARM SGP Site Atmospheric Modes of Drizzling Stratus at the ARM SGP Site Kollias, Pavlos RSMAS/University of Miami Albrecht, Bruce University of Miami The representation of boundary layer clouds in GCMs remains a source of uncertainty in climate simulations. The cloud amount in the boundary layer is sensitive to the boundary layer scheme. Furthermore, little is known on the climatology of drizzling or precipitating boundary layer clouds, their seasonal variability and

  3. ARM - Publications: Science Team Meeting Documents: Liquid water path

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    estimates in marine stratus Liquid water path estimates in marine stratus Zuidema, Paquita RSMAS/MPO University of Miami Fairall, Chris NOAA/Environmental Technology Laboratory Westwater, Ed University of Colorado/CIRES Hazen, Duane NOAA/Environmental Technology Laboratory We examine liquid water paths (LWPs) derived from ship-based microwave radiometer brightness temperature ($T_b$) measurements collected in overcast, well-mixed boundary layer conditions within the southeastern Pacific. 3

  4. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Arctic Stratus Cloud Properties and Radiaitve Forcing Derived From Ground-Based Data Collected at ARM NSA Site and SHEBA Ship Dong, X. and Mace, G.G., University of Utah Twelfth Atmospheric Radiation Measurement (ARM) Science Team Meeting A record of single-layer and overcast low-level Arctic stratus cloud properties has been generated using data collected at the Atmospheric Radiation Measurement site near Barrow, Alaska from May to September 2000. The record includes liquid-phase and liquid

  5. gottschalck(1)-99

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Macroscopic Cloud and Boundary Layer Properties for Continental Stratus at the SGP CART Site During 1997 J. C. Gottschalck and B. A. Albrecht University of Miami Miami, Florida Introduction Stratus and stratocumulus clouds are important in the regulation of the earth's radiation budget and thus play an important role in climate over both the land and ocean (Ramanathan et al. 1989). Consequently, there is a great need for accurate boundary layer cloud parameterizations in climate models (Slingo

  6. kollias-98.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    7 High Resolution Doppler Radar Observations in Continental Stratus Clouds P. Kollias and B. A. Albrecht University of Miami Miami, Florida Introduction Vertical mixing is a key factor in determining the macroscopic and microscopic structure of stratus clouds. The vertical velocities resolved from millimeter-wavelength radars can be used to define the turbulence structure within such clouds (Frisch et al. 1995). To illustrate the utility of such radar measurements for studying the turbulence

  7. liesvend-98.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    A Simple, Yet Realistic Model for the Formation of Arctic Stratus Clouds-A Case Study O. Lie-Svendsen Norwegian Defense Research Establishment Kjeller, Norway Q. Zhang, J. Simmons, and K. Stamnes Geophysical Institute University of Alaska, Fairbanks Introduction We have developed a one-dimensional radiative-convective model with detailed cloud microphysics, and used it to study the formation of Arctic Stratus clouds (ASC). The model contains detailed radiative and microphysical modules, and it

  8. zhang(1)-98.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    7 The Influence of Radiation and Large-Scale Vertical Motion on the Persistence of Arctic Stratus Clouds Q. Zhang and K. Stamnes Geophysical Institute University of Alaska Fairbanks, Alaska D. K. Lilly Cooperative Institute for Meteorological Satellite Studies University of Oklahoma Boulder, Oklahoma Introduction Arctic Stratus Clouds (ASCs) are important modulators of local climate, and perhaps even global climate. One of the most significant features of ASC is that they can persist for several

  9. zhang(2)-98.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    3 Formation of Arctic Stratus Clouds: Comparison of Model Predictions with Observed Cloud Structure Q. Zhang and K. Stamnes Geophysical Institute University of Alaska Fairbanks, Alaska O. Lie-Svendsen Norwegian Defense Research Establishment Kjeller, Norway Introduction The importance of the Arctic region to global climate has been highlighted by the climate modeling results in recent years (e.g., Manabe et al. 1991). Arctic stratus clouds (ASC) are not only one of the most significant regional

  10. zhang-q-99.PDF

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    Study of the Formation of Single- and Multiple-Layered Arctic Stratus Clouds Q. Zhang University of Utah Salt Lake City, Utah K. Stamnes and J. Harrington Geophysical Institute University of Alaska Fairbanks, Alaska O. Lie-Svendsen Norwegian Defense Research Establishment Kjeller, Norway Introduction Arctic stratus clouds (ASCs) are a persistent feature in the arctic. They may have an important influence on both the local climate and the global climate. Due to lack of observations, the formation

  11. Kato-S

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Doppler Radar and Microwave Radiometer Derived Stratus Cloud Particle Size Distributions S. Kato Center for Atmospheric Sciences Hampton University Hampton, Virginia G. G. Mace Department of Meteorology University of Utah Salt Lake City, Utah E. E. Clothiaux Department of Meteorology The Pennsylvania State University University Park, Pennsylvania J. C. Liljegren Argonne National Laboratory Argonne, Illinois Introduction Some earlier studies demonstrate that the size distribution of stratus cloud

  12. Microsoft PowerPoint - poster for ARM 2007 5

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    process in single-layer arctic stratus during MPACE Gong Zhang 1 , Greg McFarquhar 1 , Johannes Verlinde 2 , Michael Poellot 3 , Greg Kok 4 , Edwin Eloranta 5 , Paul DeMott 6 , Tony Prenni 6 and Andrew Heymsfield 7 1 University of Illinois 2 Pennsylvania State University 3 University of North Dakota 4 Droplet Measurement Technologies 5 University of Wisconsin 6 Colorado State University 7 National Center for Atmospheric Research 1 Arctic boundary single-layer stratus 2 Vertical cloud structure

  13. ARM - VAP Process - mmcrmode

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Productsmmcrmode Documentation & Plots Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP : MMCR mode moments, derived by ARSCL process (MMCRMODE) Instrument Categories Cloud Properties Output Products mmcrmode01v0011cloth : ARSCL: derived, MMCR Mode 1 (stratus mode) moments (11/96 -12/96) mmcrmode01v0021cloth : ARSCL: derived, MMCR Mode 1 (stratus mode) moments

  14. 1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Comparisons with the Cloud Radar Retrievals of Stratus Cloud Effective Radius A. S. Frisch and G. Feingold Cooperative Institute for Research in the Atmosphere National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado M. D Shupe and I. Djalalova Science Technology Corporation National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado M. R. Poellot Department of Atmospheric Sciences University of North Dakota

  15. frisch(2)-99.PDF

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Radar/Radiometer Retrievals of Stratus Cloud Liquid Water Content Profiles with In Situ Measurements by Aircraft A. S. Frisch Cooperative Institute for Research in the Atmosphere Colorado State University Boulder, Colorado B. E. Martner National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado I. Djalalova Science Technology Corporation Albuquerque, New Mexico M. R. Poellot Department of Atmospheric Sciences University of North Dakota Grand Forks,

  16. X:\ARM_19~1\P377-392.WPD

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    1 2 ÷2.5 km R LWP VarR LWP Session Papers 389 Albedo and Transmittance of Inhomogeneous Stratus Clouds V. E. Zuev, E. I. Kasyanov, and G. A. Titov Institute of Atmospheric Optics, Russian Academy of Sciences Tomsk, Russia S. M. Prigarin Computer Center, Russian Academy of Sciences Novosibirsk, Russia A highly important topic of recent concern has been the The statistical characteristics describing the fluctuations of study of the relationship between the statistical parameters of optical and

  17. X:\ARM_19~1\PG93-112.WPD

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Figure 1. Drizzle parameters. The data for these measurements were taken on June 6, 1992, at 6 am. The first three Doppler moments from the vertically pointing radar were used in a log-normal three parameter cloud droplet model to determine the vertical profiles of modal radius, the standard deviation, and the number of droplets. Island Based Radar and Microwave Radiometer Measurements of Stratus Cloud Parameters During the Atlantic Stratocumulus Transition Experiment (ASTEX) A. S. Frisch C. W.

  18. The influence of ice nucleation mode and ice vapor growth on simulation of

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    arctic mixed-phase clouds The influence of ice nucleation mode and ice vapor growth on simulation of arctic mixed-phase clouds Avramov, Alexander The Pennsylvania State University Category: Modeling Mixed-phase arctic stratus clouds are the predominant cloud type in the Arctic . Perhaps one of the most intriguing of their features is that they tend to have liquid tops that precipitate ice. Despite the fact that this situation is colloidally unstable, these cloud systems are quite long lived

  19. 1

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    Breakup of Stratus Cloud Structure Predicted from Non-Brownian Motion Liquid Water Fluctuations K. Ivanova Department of Meteorology Pennsylvania State University University Park, Pennsylvania and Institute of Electronics Bulgarian Academy Sciences Sofia, Bulgaria M. Ausloos SUPRAS and GRASP Institute of Physics Liege, Belgium E. E. Clothiaux and H. N. Shirer Department of Meteorology Pennsylvania State University University Park, Pennsylvania T. P. Ackerman Pacific Northwest National Laboratory

  20. Posters

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    9 Posters Stratus Cloud Measurements with a K α -Band Doppler Radar and a Microwave Radiometer A. S. Frisch, C. W. Fairall, and J. B. Snider National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado D. H. Lenschow National Center for Atmospheric Research Boulder, Colorado The goal of the Atlantic Stratocumulus Transition Experiment (ASTEX) held in the North Atlantic during June 1992 was to determine the physical reasons for the transition from

  1. Posters

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    3 Posters The Effects of Arctic Stratus Clouds on the Solar Energy Budget in the Atmosphere-Sea Ice-Ocean System Z. Jin and K. Stamnes Geophysical Institute University of Alaska Fairbanks, Alaska B. D. Zak Sandia National Laboratories Albuquerque, New Mexico Radiative Transfer Model We have developed a comprehensive radiative transfer model pertinent to the atmosphere-sea ice-ocean system (Jin and Stamnes 1994; Jin et al., in press). The main features of the newly-developed radiative transfer

  2. ARM - VAP Product - mmcrmode01v0011cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    11cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027297 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0011CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (11/96 -12/96) Active Dates 1996.11.08 - 1997.03.28

  3. ARM - VAP Product - mmcrmode01v0021cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    21cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027298 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0021CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (2/97) Active Dates 1997.02.26 - 1997.02.26

  4. ARM - VAP Product - mmcrmode01v0031cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    31cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027300 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0031CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (3/97) Active Dates 1997.03.29 - 1997.03.31

  5. ARM - VAP Product - mmcrmode01v0041cloth

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    41cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027301 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0041CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (4/97-9/97) Active Dates 1997.04.01 - 1997.09.1

  6. ARM - VAP Product - mmcrmode01v0051cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    51cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027302 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0051CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (12/96-2/97) Active Dates 1996.12.02 - 1997.02.2

  7. ARM Aerosol Working Group Meeting

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Report ARM STM 2008 Norfolk, VA Connor Flynn for B Schmid and AWG Members AWG Instruments * Raman Lidar - SGP * Micropulse Lidars - all sites * Aerosol Sampling - SGP, NSA, AMF - scattering, absorption, number, size distribution, hygroscopicity, CCN, composition (major ions). * In situ Aerosol Profile (Cessna) - scattering, absorption, number, hygroscopicity, * Radiometers: - MFRSR, NIMFR, RSS, Cimel, AERI, SWS AWG-related Field Campaigns * Recent Past: - MASRAD (Marine Stratus Radiation,

  8. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Radiative Properties of Uniform and Broken Stratus: An Observational and Modelling Study Utilizing the Independent Column Approximation for Solar Radiative Transfer Clothiaux, E.E., The Pennsylvania State University; Barker, H.W., Atmospheric Environment Service of Canada; Kato, S., Hampton University; Dong, X., Analytical Service and Materials, Inc. Ackerman, T.P., The Pennsylvania State University; Liljegren, J.C., Ames Laboratory Ninth Atmospheric Radiation Measurement (ARM) Science Team

  9. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    An Integrated Algorithm for Retrieving Low-Level Stratus Cloud Microphysical Properties Using Millimeter Radar and Microwave Radiometer Data Dong, X. and Mace, G.G., University of Utah Twelfth Atmospheric Radiation Measurement (ARM) Science Team Meeting Two methods have been developed for inferring the vertical profiles of cloud microphysics in liquid phase stratocumulus clouds. The first method uses cloud liquid water path derived from microwave radiometer observations and a profile of radar

  10. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Climatology of Stratus Clouds at the SGP: A Radiation Based Study Sengupta, M.(a), Ackerman, T.P.(a), and Clothiaux, E.E.(b), Pacific Northwest National Laboratory (a), The Pennsylvania State University (b) Twelfth Atmospheric Radiation Measurement (ARM) Science Team Meeting The Atmospheric Radiation Measurement (ARM) program is a source of continuous data that can be used for various short-term climatological studies. Using multiple datasets from ARM for the Southern Great Plains (SGP) Central

  11. ARM - Publications: Science Team Meeting Documents

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Comparison of Observed and Modelled Liquid Water Path for Stratus and Stratocumulus Clouds at the SGP Sengupta,M.(a), Ackerman,T.P.(a), and Clothiaux,E.E.(b), Pacific Northwest National Laboratory (a), The Pennsylvania State University (b) Thirteenth Atmospheric Radiation Measurement (ARM) Science Team Meeting Accurate representation of observations in models is a integral part of improving model accuracy. With the availability of long-term data sets from ARM it is possible to statistical

  12. Hierarchical Diagnosis

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Development of a Rad iative Cloud Parameterization Scheme of Stratocumulus and Stratus Clouds Which Includes the Impact of Cloud Condensation Nucleus on Cloud Albedo W. R. Cotton, G. L. Stephens, D. Duda, B. Stevens, and R. L. Walko Colorado State University Department of Atmospheric Science Fort Collins, CO G. Feingold Cooperative Institute for Research in Environmental Sciences University of Colorado, Boulder Boulder. CO 80309-0049 A three-dimensional (3-D) model for simulating the effect of

  13. Hierarchical Diagnosis R. A. Kropfli, S. Y. Matrosov, T. Uttal, and B. W. Orr

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    R. A. Kropfli, S. Y. Matrosov, T. Uttal, and B. W. Orr National Oceanic and Atmospheric Administration/Environmental Research Laboratories Wave Propagation Laboratory Boulder, CO 80303 I ntrod uction The WPL 8-mm wavelength radar was designed with good sensitivity and resolution to observe the small-scale structure and microphysical properties of clouds. DuringASTEX, for example, it observed, with 37-m resolution, all marine boundary layer (MBL) stratus and stratocumulus clouds within 5 km of

  14. kollias-99.PDF

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Mass Flux Representations of Vertical Velocity Fluctuations in Continental Stratus Clouds Using a mm-Wavelength Doppler Radar P. Kollias and B. A. Albrecht University of Miami Miami, Florida Introduction A cloud mass flux representation of the vertical turbulent fluxes provides a physical framework for understanding the effects of shallow convection in maintaining the vertical structure of the boundary layer. This approach is based on the assumption that coherent updrafts and downdraft

  15. leoles_poster_v1.0.ppt

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Observations and LES of Liquid Stratus over the ACRF D. B. Mechem and Y. L. Kogan Cooperative Institute for Mesoscale Meteorological Studies, The University of Oklahoma The evolution of low cloud systems is inextricably linked to dynamical processes: heat, moisture, mass, and momentum transports, and of course, entrainment. Studies employing continuous years of low cloud observations over the southern great plains ARM Climate Research Facility (ACRF) emphasized their climatological,

  16. Four-Dimensional Data Assimilation D. Westphal, B. Toon, E. Jensen, S. Kinne, A. Ackerman,

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    D. Westphal, B. Toon, E. Jensen, S. Kinne, A. Ackerman, R. Bergstrom, and A. Walker National Aeronautics and Space Administration Ames Research Center Moffett Field, CA 94035 Introduction Atmospheric Radiation Measurement (ARM) Program research at NASA Ames Research Center (ARC) includes radiative transfer modeling, cirrus cloud microphysics, and stratus cloud modeling. These efforts are designed to provide the basis for improving cloud and radiation parameterizations in our main effort:

  17. Lesson Plan

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    K-2 Common Covering Clouds http://education.arm.gov Common Covering Clouds: Grades K-2 1 Common Covering Clouds Approximate Time 1 1/2 hours, or two 45-minute segments Objective The student will investigate and demonstrate understanding of common clouds as evidenced by completion of activity. Key Points to Understand * There are many types of clouds, including cirrus, cumulus, stratus, cirrocumulus, altocumulus, stratocumulus, cumulonimbus, and altostratus. * Clouds influence weather. * Weather

  18. Khaiyer.ARM.07.ppt

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    GOES-10 Satellite-derived Cloud and Radiative Properties for the MASRAD ARM Mobile Facility Deployment M. M. Khaiyer, D. R. Doelling, R. Palikonda, M.L.Nordeen Science Systems and Applications Inc, Hampton, VA P. Minnis NASA Langley Research Center, Hampton, VA 1.Introduction The ARM Mobile Facility (AMF) deployment at Pt Reyes, CA as part of the Marine Stratus Radiation Aerosol and Drizzle experiment (MASRAD), 14 March -14 September 2005 provided an excellent chance to validate satellite

  19. Kogan-ZN

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Drop Effective Radius for Drizzling Marine Stratus in Global Circulation Models Z. N. Kogan and Y. L. Kogan Cooperative Institute for Mesoscale Meteorological Studies University of Oklahoma Norman, Oklahoma Introduction The cloud drop effective radius, R e , is one of the most important parameters in calculations of cloud radiative properties. Numerous formulations of the effective radius have been developed for use in numerical models (see, e.g., review in Gultepe et al. 1996); however, to the

  20. Microsoft Word - Poellot-MR.doc

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Measurements of Cloud Liquid Water Over the SGP Site M. R. Poellot University of North Dakota Grand Forks, North Dakota R. T. Marchand Pacific Northwest National Laboratory Richland, Washington C. Twohy Oregon State University Corvallis, Oregon Introduction The University of North Dakota Citation aircraft made in situ measurements of liquid water clouds on six flights in stratus clouds during the Spring 2000 Cloud Intensive Operational Period (IOP) at the Southern Great Plains (SGP) site. Four

  1. Microsoft PowerPoint - ShupeARM2007.ppt [Compatibility Mode]

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    and Microphysics in Arctic Mixed-Phase Stratus Matthew Shupe With contributions from Pavlos Kollias, Ed Luke, Ola Persson, Greg McFarquhar, Michael Poellot, Ed Eloranta g q , , John Daniel, Gijs DeBoer, Chuck Long, Dave Turner Hans Verlinde, Amy Solomon ARM Science Team Meeting 2007 Topics Status of Ground-Based Observational Methods Observational Methods Cloud Classification Cloud Classification M-PACE M PACE Vertical Motions & Microphysics p y A Conceptual Model p Status of Ground-based

  2. Electricity Advisory Committee

    Office of Environmental Management (EM)

    Richard Cowart Committee Chair Regulatory Assistance Project Sonny Popowsky Committee Vice Chair Pennsylvania Consumer Advocate (Ret.) Ake Almgren Orkas Inc. William Ball Southern Company Anjan Bose Washington State University Marilyn Brown Georgia Institute of Technology Merwin Brown California Institute for Energy and Environment Paul Centolella The Analysis Group Carlos Coe Millennium Energy Robert Curry Jr. CurryEnergy Clark Gellings Electric Power Research Institute Paul Hudson Stratus

  3. ARM - VAP Product - mmcrmode01v0061cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    61cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027303 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0061CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (9/97-3/04) Active Dates 1997.09.15 - 2004.03.17 Originating VAP Process MMCR mode moments, derived by ARSCL process : MMCRMODE Measurements The

  4. ARM - VAP Product - mmcrmode01v0071cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    71cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027304 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0071CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (11/98-9/02) Active Dates 1998.11.01 - 2002.09.21 Originating VAP Process MMCR mode moments, derived by ARSCL process : MMCRMODE Measurements The

  5. ARM - VAP Product - mmcrmode01v0091cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    91cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027305 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE01V0091CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments (3/98-4/04) Active Dates 1998.03.25 - 2004.04.13 Originating VAP Process MMCR mode moments, derived by ARSCL process : MMCRMODE Measurements The

  6. ARM - VAP Product - mmcrmode1st200404151cloth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    404151cloth Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027334 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : MMCRMODE1ST200404151CLOTH ARSCL: derived, MMCR Mode 1 (stratus mode) moments, 20040415 version Active Dates 2004.04.15 - 2007.11.27 Originating VAP Process MMCR mode moments, derived by ARSCL process : MMCRMODE

  7. Impact of aerosol on mixed-phase stratocumulus during MPACE in a mesoscale

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    model with two-moment microphysics Impact of aerosol on mixed-phase stratocumulus during MPACE in a mesoscale model with two-moment microphysics Morrison, Hugh MMM/ASP National Center for Atmospheric Research Pinto, James University of Colorado Curry, Judith Georgia Institute of Technology Category: Modeling The Penn State/NCAR mesoscale model MM5 is coupled to a new microphysics scheme to examine the impact of aerosol on mixed-phase stratocumulus during the Mixed-Phase Arctic Stratus

  8. Microsoft PowerPoint - ARMST2007_mp.ppt

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    in Arctic Mixed-Phase Stratus Matthew D. Shupe a , Pavlos Kollias b , Ola Persson a , Ed Luke b Greg McFarquhar c , Michael Poellot d , Edwin Eloranta e a CIRES - University of Colorado and NOAA/ESRL/PSD, b Brookhaven National Laboratory, c University of Illinois, d University of North Dakota, e University of Wisonsin Mixed-Phase Cloud Properties Air Motions from Doppler Spectra Funded by: ARM Grant DE-FG02-05ER63965 Summary A Conceptual Model relating air motions and microphysics A Doppler

  9. Final technical Report DE-FG02-06ER65187

    SciTech Connect (OSTI)

    Edwin Eloranta

    2009-07-17

    Simulations from the University of Wisconsin Non-Hydrostatic Modeling System (UW-NMS) along with those from other models indicate a strong tendency to overproduce ice, resulting in a decimation of the liquid portion of mixed-phase stratus through the Bergeron-Findeissen process. Immersion freezing was illustrated to be a major contributor to ice production within these cloud layers, and aerosol properties were illustrated to be an important consideration in the simulation of this process. In particular, the soluble mass fraction and aerosol insoluble mass type were demonstrated to influence simulation of the immersion freezing process, Data collected by the Arctic High Spectral Resolution Lidar and Millimeter Cloud Radar during the M-PACE period was analyzed in order to provide a statistical dataset for validation of simulations of mixed-phase stratus. 270 hours of single-layer cases were reviewed, and mean values for cloud base height, cloud thickness, cloud optical thickness, cloud temperature, wind direction, and liquid and ice particle size, particle number density, and water content were derived.

  10. Coupling Between Oceanic Upwelling and Cloud-aerosol Properties at the AMF Point Reyes Site

    SciTech Connect (OSTI)

    Dunn, M.; Jensen, M.; Miller, M.; Kollias, P.; Bartholomew, M. J.; Turner, D.; Andrews, E.; Jefferson, A.; Daum, P.

    2008-03-10

    Cloud microphysical properties measured at the ARM Mobile Facility site located on the northern coast of California near Point Reyes, during the 2005 Marine Stratus Radiation, Aerosol and Drizzle experiment, were analyzed to determine their relationship to the coastal sea surface temperature (SST) which was characterized using measurements acquired from a National Oceanic and Atmospheric Administration offshore buoy. An increase in SST resulting from a relaxation of upwelling, occurring in the eastern Pacific Ocean off the coast of California in summer is observed to strongly correlate with nearby ground measured cloud microphysical properties and cloud condensation nuclei (CCN) concentrations. Correlations between these atmospheric and oceanic features provide insight into the interplay between the ocean and cloud radiative properties. We present evidence of this robust correlation and examine the factors controlling these features. The marine boundary layer is in direct contact with the sea surface and is strongly influenced by SST. Moisture and vertical motion are crucial ingredients for cloud development and so we examine the role of SST in providing these key components to the atmosphere. Although upwelling of cold subsurface waters is conventionally thought to increase aerosols in the region, thus increasing clouds, here we observed a relaxation of upwelling associated with changes in the structure of marine stratus clouds. As upwelling relaxes, the SST get warmer, thick clouds with high liquid water paths are observed and persist for a few days. This cycle is repeated throughout the summer upwelling season. A concomitant cyclic increase and decrease of CCN concentration is also observed. Forcing mechanisms and large-scale atmospheric features are discussed. Marine stratocumulus clouds are a critical component of the earth's radiation budget and this site provides an excellent opportunity to study the influence of SST on these clouds.

  11. Boundary Layer Cloudiness Parameterizations Using ARM Observations

    SciTech Connect (OSTI)

    Bruce Albrecht

    2004-09-15

    This study used DOE ARM data and facilities to: (1) study macroscopic properties of continental stratus clouds at SGP and the factors controlling these properties, (2) develop a scientific basis for understanding the processes responsible for the formation of boundary layer clouds using ARM observations in conjunction with simple parametric models and LES, and (3) evaluate cumulus cloud characteristics retrieved from the MMCR operating at TWP-Nauru. In addition we have used high resolution 94 GHz observations of boundary layer clouds and precipitation to: (1) develop techniques for using high temporal resolution Doppler velocities to study large-eddy circulations and turbulence in boundary layer clouds and estimate the limitations of using current and past MMCR data for boundary layer cloud studies, (2) evaluate the capability and limitations of the current MMCR data for estimating reflectivity, vertical velocities, and spectral under low- signal-to-noise conditions associated with weak no n-precipitating clouds, (3) develop possible sampling modes for the new MMCR processors to allow for adequate sampling of boundary layer clouds, and (4) retrieve updraft and downdraft structures under precipitating conditions.

  12. Final Technical Report ARM DOE Grant #DE-FG02-03ER63520 Parameterizations of Shortwave Radiactive Properties of Broken Clouds from Satellite and Ground-Based Measurements

    SciTech Connect (OSTI)

    Albrecht, Bruce, A.

    2006-06-19

    This study used DOE ARM data and facilities to: 1) study macroscopic properties of continental stratus clouds at SGP and the factors controlling these properties, 2) develop a scientific basis for understanding the pocesses responsible for the formation of boundary layer clouds using ARM observations in conjunction with simple parametric models and LES, and 3) evaluate cumulus cloud characteristics retrieved retrieved from the MMCR operating at TWP-Nauru. In addition we have used high resolution 94 GHz observations of boundary layer clouds and precipitation to: 1)develop techniques for using high temporal resolution Doppler velocities to study large-eddy circulations and turbulence in boundary layer clouds and estimate the limitations of using current and past MMCR data for boundary layer cloud studies, 2) evaluate the capability and limitation of the current MMCR data for estimating reflectivity, vertical velocities, and spectral under low-signal-to-noise conditions associated with weak non-precipitating clouds, 3) develop possible sampling modes for the new MMCR processors to allow for adequate sampling of boundary layer clouds, and 4) retrieve updraft and downdraft structures under precipitating conditions.

  13. Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds"? (DOE/SC00002354)

    SciTech Connect (OSTI)

    Paul J. DeMott, Anthony J. Prenni; Sonia M. Kreidenweis

    2012-09-28

    Clouds play an important role in weather and climate. In addition to their key role in the hydrologic cycle, clouds scatter incoming solar radiation and trap infrared radiation from the surface and lower atmosphere. Despite their importance, feedbacks involving clouds remain as one of the largest sources of uncertainty in climate models. To better simulate cloud processes requires better characterization of cloud microphysical processes, which can affect the spatial extent, optical depth and lifetime of clouds. To this end, we developed a new parameterization to be used in numerical models that describes the variation of ice nuclei (IN) number concentrations active to form ice crystals in mixed-phase (water droplets and ice crystals co-existing) cloud conditions as these depend on existing aerosol properties and temperature. The parameterization is based on data collected using the Colorado State University continuous flow diffusion chamber in aircraft and ground-based campaigns over a 14-year period, including data from the DOE-supported Mixed-Phase Arctic Cloud Experiment. The resulting relationship is shown to more accurately represent the variability of ice nuclei distributions in the atmosphere compared to currently used parameterizations based on temperature alone. When implemented in one global climate model, the new parameterization predicted more realistic annually averaged cloud water and ice distributions, and cloud radiative properties, especially for sensitive higher latitude mixed-phase cloud regions. As a test of the new global IN scheme, it was compared to independent data collected during the 2008 DOE-sponsored Indirect and Semi-Direct Aerosol Campaign (ISDAC). Good agreement with this new data set suggests the broad applicability of the new scheme for describing general (non-chemically specific) aerosol influences on IN number concentrations feeding mixed-phase Arctic stratus clouds. Finally, the parameterization was implemented into a regional cloud-resolving model to compare predictions of ice crystal concentrations and other cloud properties to those observed in two intensive case studies of Arctic stratus during ISDAC. Our implementation included development of a prognostic scheme of ice activation using the IN parameterization so that the most realistic treatment of ice nuclei, including their budget (gains and losses), was achieved. Many cloud microphysical properties and cloud persistence were faithfully reproduced, despite a tendency to under-predict (by a few to several times) ice crystal number concentrations and cloud ice mass, in agreement with some other studies. This work serves generally as the basis for improving predictive schemes for cloud ice crystal activation in cloud and climate models, and more specifically as the basis for such a scheme to be used in a Multi-scale Modeling Format (MMF) that utilizes a connected system of cloud-resolving models on a global grid in an effort to better resolve cloud processes and their influence on climate.

  14. Contribution to the development of DOE ARM Climate Modeling Best Estimate Data (CMBE) products: Satellite data over the ARM permanent and AMF sites: Final Report

    SciTech Connect (OSTI)

    Xie, B; Dong, X; Xie, S

    2012-05-18

    To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky and clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.

  15. Indirect and Semi-Direct Aerosol Campaign: The Impact of Arctic Aerosols on Clouds

    SciTech Connect (OSTI)

    McFarquhar, Greg; Ghan, Steven J.; Verlinde, J.; Korolev, Alexei; Strapp, J. Walter; Schmid, Beat; Tomlinson, Jason M.; Wolde, Mengistu; Brooks, Sarah D.; Cziczo, Daniel J.; Dubey, Manvendra K.; Fan, Jiwen; Flynn, Connor J.; Gultepe, Ismail; Hubbe, John M.; Gilles, Mary K.; Laskin, Alexander; Lawson, Paul; Leaitch, W. R.; Liu, Peter S.; Liu, Xiaohong; Lubin, Dan; Mazzoleni, Claudio; Macdonald, A. M.; Moffet, Ryan C.; Morrison, H.; Ovchinnikov, Mikhail; Shupe, Matthew D.; Turner, David D.; Xie, Shaocheng; Zelenyuk, Alla; Bae, Kenny; Freer, Matthew; Glen, Andrew

    2011-02-01

    A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the arctic boundary layer in the vicinity of Barrow, Alaska was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) sponsored by the Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric Science Programs. The primary aim of ISDAC was to examine indirect effects of aerosols on clouds that contain both liquid and ice water. The experiment utilized the ARM permanent observational facilities at the North Slope of Alaska (NSA) in Barrow. These include a cloud radar, a polarized micropulse lidar, and an atmospheric emitted radiance interferometer as well as instruments specially deployed for ISDAC measuring aerosol, ice fog, precipitation and spectral shortwave radiation. The National Research Council of Canada Convair-580 flew 27 sorties during ISDAC, collecting data using an unprecedented 42 cloud and aerosol instruments for more than 100 hours on 12 different days. Data were obtained above, below and within single-layer stratus on 8 April and 26 April 2008. These data enable a process-oriented understanding of how aerosols affect the microphysical and radiative properties of arctic clouds influenced by different surface conditions. Observations acquired on a heavily polluted day, 19 April 2008, are enhancing this understanding. Data acquired in cirrus on transit flights between Fairbanks and Barrow are improving our understanding of the performance of cloud probes in ice. Ultimately the ISDAC data will be used to improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and to determine the extent to which long-term surface-based measurements can provide retrievals of aerosols, clouds, precipitation and radiative heating in the Arctic.

  16. Efficacy of Aerosol-Cloud Interactions Under Varying Meteorological Conditions: Southern Great Plains Vs. Pt. Reyes

    SciTech Connect (OSTI)

    Dunn, M.; Schwartz, S.; Kim, B.-G.; Miller, M.; Liu, Y.; Min, Q.

    2008-03-10

    Several studies have demonstrated that cloud dynamical processes such as entrainment mixing may be the primary modulator of cloud optical properties in certain situations. For example, entrainment of dry air alters the cloud drop size distribution by enhancing drop evaporation. However, the effect of entrainment mixing and other forms or turbulence is still quite uncertain. Although these factors and aerosol-cloud interactions should be considered together when evaluating the efficacy of aerosol indirect effects, the underlying mechanisms appear to be dependent upon each other. In addition, accounting for them is impossible with the current understanding of aerosol indirect effect. Therefore, careful objective screening and analysis of observations are needed to determine the extent to which mixing related properties affect cloud optical properties, apart from the aerosol first indirect effect. This study addresses the role of aerosol-cloud interactions in the context of varying meteorological conditions based on ARM data obtained at the Southern Great Plains (SGP) site in Oklahoma and at Pt. Reyes, California. Previous analyses of the continental stratiform clouds at the SGP site have shown that the thicker clouds of high liquid water path (LWP) tend to contain sub adiabatic LWPs. These sub adiabatic LWPs, which result from active mixing processes, correspond to a lower susceptibility of the clouds to aerosol-cloud interactions, and, hence, to reduced aerosol indirect effects. In contrast, the consistently steady and thin maritime stratus clouds observed at Pt. Reyes are much closer to adiabatic. These clouds provide an excellent benchmark for the study of the aerosol influence on modified marine clouds relative to continental clouds, since they form in a much more homogeneous meteorological environment than those at the continental site.

  17. NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System

    SciTech Connect (OSTI)

    Tribbia, Joseph

    2015-11-25

    NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate System Model version 4 (CCSM4). Compared to CCSM4, the new coupled model has a superior climate response with respect to low clouds in both the subtropical stratus regimes and the Arctic. However, CESM1 has been run to date using a prognostic aerosol model that more than doubles its computational cost. We are currently evaluating a version of the new model using prescribed aerosols and expect it will be ready for integrations in summer 2012. Because of this NCAR has not been able to complete the hindcast integrations using the NCAR loosely-coupled ensemble Kalman filter assimilation method nor has it contributed to the current (Stage I) NMME operational utilization. The expectation is that this model will be included in the NMME in late 2012 or early 2013. The initialization method will utilize the Ensemble Kalman Filter Assimilation methods developed at NCAR using the Data Assimilation Research Testbed (DART) in conjunction with Jeff Anderson’s team in CISL. This methodology has been used in our decadal prediction contributions to CMIP5. During the course of this project, NCAR has setup and performed all the needed hindcast and forecast simulations and provide the requested fields to our collaborators. In addition, NCAR researchers have participated fully in research themes (i) and (ii). Specifically, i) we have begun to evaluate and optimize our system in hindcast mode, focusing on the optimal number of ensemble members, methodologies to recalibrate individual dynamical models, and accessing our forecasts across multiple time scales, i.e., beyond two weeks, and ii) we have begun investigation of the role of different ocean initial conditions in seasonal forecasts. The completion of the calibration hindcasts for Seasonal to Interannual (SI) predictions and the maintenance of the data archive associated with the NCAR portion of this effort has been the responsibility of the Project Scientist I (Alicia Karspeck) that was partially supported on this project.

  18. Chemical Composition and Sources of Coastal Marine Aerosol Particles during the 2008 VOCALS-REx Campaign

    SciTech Connect (OSTI)

    Lee, Y.- N.; Springston, S.; Jayne, John T.; Wang, Jian; Hubbe, John M.; Senum, Gunnar I.; Kleinman, Lawrence I.; Daum, Peter H.

    2014-05-23

    The chemical composition of aerosol particles (Dp 1.5 ?m) was measured over the southeast Pacific Ocean during the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-Rex) between 16 October and 15 November 2008 using the US Department of Energy (DOE) G-1 aircraft. The objective of these flights was to gain an understanding of the sources and evolution of these aerosols, and of how they interact with the marine stratus cloud layer that prevails in this region of the globe. Our measurements showed that the marine boundary layer (MBL) aerosol mass was dominated by non-sea-salt SO2?4, followed by Na+, Cl?, Org (total organics), NH+4 , and NO?3 , in decreasing order of importance; CH3SO?3 (MSA), Ca2+, and K+ rarely exceeded their limits of detection. Aerosols were strongly acidic with a NH+4 to SO2?4 equivalents ratio typically < 0.3. Sea-salt aerosol (SSA) particles, represented by NaCl, exhibited Cl? deficits caused by both HNO3 and H2SO4, but for the most part were externally mixed with particles, mainly SO2?4. SSA contributed only a small fraction of the total accumulation mode particle number concentration. It was inferred that all aerosol species (except SSA) were of predominantly continental origin because of their strong land-to-sea concentration gradient. Comparison of relative changes in median values suggests that (1) an oceanic source of NH3 is present between 72 W and 76 W, (2) additional organic aerosols from biomass burns or biogenic precursors were emitted from coastal regions south of 31 S, with possible cloud processing, and (3) free tropospheric (FT) contributions to MBL gas and aerosol concentrations were negligible. The very low levels of CH3SO?3 observed as well as the correlation between SO2?4 and NO?3 (which is thought primarily anthropogenic) suggest a limited contribution of DMS to SO2?4 aerosol production during VOCALS.

  19. The Radiative Role of Free Tropospheric Aerosols and Marine Clouds over the Central North Atlantic

    SciTech Connect (OSTI)

    Mazzoleni, Claudio; Kumar, Sumit; Wright, Kendra; Kramer, Louisa; Mazzoleni, Lynn; Owen, Robert; Helmig, Detlev

    2014-12-09

    The scientific scope of the project was to exploit the unique location of the Pico Mountain Observatory (PMO) located in the summit caldera of the Pico Volcano in Pico Island in the Azores, for atmospheric studies. The observatory, located at 2225m a.s.l., typically samples free tropospheric aerosols laying above the marine low-level clouds and long-range transported from North America. The broad purpose of this research was to provide the scientific community with a better understanding of fundamental physical processes governing the effects of aerosols on radiative forcing and climate; with the ultimate goal of improving our abilities to understand past climate and to predict future changes through numerical models. The project was 'exploratory' in nature, with the plan to demonstrate the feasibility of deploying for the first time, an extensive aerosol research package at PMO. One of the primary activities was to test the deployment of these instruments at the site, to collect data during the 2012 summer season, and to further develop the infrastructure and the knowledge for performing novel research at PMO in follow-up longer-term aerosol-cloud studies. In the future, PMO could provide an elevated research outpost to support the renewed DOE effort in the Azores that was intensified in 2013 with the opening of the new sea-level ARM-DOE Eastern North Atlantic permanent facility at Graciosa Island. During the project period, extensive new data sets were collected for the planned 2012 season. Thanks to other synergistic activities and opportunities, data collection was then successfully extended to 2013 and 2014. Highlights of the scientific findings during this project include: a) biomass burning contribute significantly to the aerosol loading in the North Atlantic free troposphere; however, long-range transported black carbon concentrations decreased substantially in the last decade. b) Single black carbon particles analyzed off-line at the electron microscope were often very compacted, suggesting cloud processing and exhibiting different optical properties from fresh emissions. In addition, black carbon was found to be sometimes mixed with mineral dust, affecting its optical properties and potential forcing. c) Some aerosols collected at PMO acted as ice nuclei, potentially contributing to cirrus cloud formation during their transport in the upper free troposphere. Identified good ice nuclei were often mineral dust particles. d) The free tropospheric aerosols studied at PMO have relevance to low level marine clouds due, for example, to synoptic subsidence entraining free tropospheric aerosols into the marine boundary layer. This has potentially large consequences on cloud condensation nuclei concentrations and compositions in the marine boundary layer; therefore, having an effect on the marine stratus clouds, with potentially important repercussions on the radiative forcing. The scientific products of this project currently include contributions to two papers published in the Nature Publishing group (Nature Communications and Scientific Reports), one paper under revision for Atmospheric Chemistry and Physics, one in review in Geophysical Research Letters and one recently submitted to Atmospheric Chemistry and Physics Discussion. In addition, four manuscripts are in advanced state of preparation. Finally, twenty-eight presentations were given at international conferences, workshops and seminars.

  20. A Seasonal Perspective on Regional Air Quality in CentralCalifornia - Phase 1

    SciTech Connect (OSTI)

    Harley, Robert A.; Brown, Nancy J.; Tonse, Shaheen R.; Jin, Ling

    2006-12-01

    Central California spans a wide variety of urban, agricultural, and natural terrain, including the San Francisco Bay area, the Central Valley, and the Sierra Nevada Mountains. Population within this region is growing rapidly, and there are persistent, serious air pollution problems including fine particulate matter (PM{sub 2.5}) and ozone. Summertime photochemical air pollution is the focus of the present study, which represents a first phase in the development and application of a modeling capability to assess formation and transport of ozone and its precursors within Central California over an entire summer season. This contrasts with past studies that have examined pollutant dynamics for a few selected high-ozone episodes each lasting 3-5 days. The Community Multiscale Air Quality model (CMAQ) has been applied to predict air pollutant formation and transport in Central California for a 15-day period beginning on July 24, 2000. This period includes a 5-day intensive operating period (July 29 to August 2) from the Central California Ozone Study (CCOS). Day-specific meteorological conditions were modeled by research collaborators at NOAA using a mesoscale meteorological model (MM5). Pollutant emissions within the study domain were based on CARB emission inventory estimates, with additional efforts conducted as part of this research to capture relevant emissions variability including (1) temperature and sunlight-driven changes in biogenic VOC, (2) weekday/weekend and diurnal differences in light-duty (LD) and heavy-duty (HD) motor vehicle emissions, (3) effects of day-specific meteorological conditions on plume rise from point sources such as power plants. We also studied the effects of using cleaner pollutant inflow boundary conditions, lower than indicated during CCOS aircraft flights over the Pacific Ocean, but supported by other surface, ship-based, balloon and aircraft sampling studies along the west coast. Model predictions were compared with measured concentrations for O{sub 3}, NO{sub x}, NO{sub y}, and CO at about 100 ground observation stations within the CCOS domain. Comparisons were made both for time series and for statistically aggregated metrics, to assess model performance over the whole modeling domain and for the individual air basins within the domain. The model tends to over-predict ozone levels along the coast where observed levels are generally low. Inland performance in the San Joaquin Valley is generally better. Model-measurement agreement for night-time ozone is improved by evaluating the sum of predicted O{sub 3} + NO{sub 2} against observations; this removes from the comparison the effect of any ozone titration that may occur. A variety of diagnostic simulations were conducted to investigate the causes for differences between predictions and observations. These included (1) enhanced deposition of O{sub 3} to the ocean, (2) reduced vertical mixing over the ocean, (3) attenuation of sunlight by coastal stratus, (4) the influence of surface albedo on photochemistry, and (5) the effects of observation nudging on wind fields. Use of advanced model probing tools such as process analysis and sensitivity analysis is demonstrated by diagnosing model sensitivity to boundary conditions and to weekday-weekend emission changes.

  1. Computing for Finance

    ScienceCinema (OSTI)

    None

    2011-10-06

    The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing ? from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with "Seti@Home". Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege o

  2. Use of ARM Products in Reanalysis Applications and IPCC Model Assessment

    SciTech Connect (OSTI)

    Walsh, John E; Chapman, William L

    2011-09-30

    Year-3 of the project was spent developing an observed cloud climatology for Barrow, AK and relating the observed cloud fractions to the surface circulation patterns and locally observed winds. Armed with this information, we identified errors and sources of errors of cloud fraction simulations by numerical models in the Arctic. Specifically, we compared the cloud simulations output by the North American Regional Reanalysis (NARR) to corresponding observed cloud fractions obtained by the Department of Energy’s Atmospheric Radiation Measurement (ARM) program for four mid-season months: (January, April, July, and October). Reanalyses are obtained from numerical weather prediction models that are not run in real-time. Instead, a reanalysis model ingests a wide variety of historical observations for the purpose of producing a gridded dataset of many model-derived quantities that are as temporally homogeneous as possible. Therefore, reanalysis output can be used as a proxy for observations, although some biases and other errors are inevitable because of model parameterizations and observational gaps. In the observational analysis we documented the seasonality of cloudiness at the north slope including cloud base height and dependence on synoptic regime. We followed this with an evaluation of the associations of wind-speed and direction and cloud amounts in both the observational record and the reanalysis model. The Barrow cloud fraction data show that clear conditions are most often associated with anomalous high pressure to the north of Barrow, especially in spring and early summer. Overcast skies are most commonly associated with anomalous low pressure to the south. The observational analysis shows that low, boundary layer clouds are the most common type of cloud observed North Slope ARM observing site. However, these near-surface clouds are a major source of errors in the NARR simulations. When compared to observations, the NARR over-simulates the fraction of low clouds during the winter months, and under-simulates the fraction of low clouds during the summer months. The NARR wind speeds at the North Slope are correlated to the observed ARM wind speeds at Barrow. The following correlations were obtained using the 3-hourly data: Jan (0.84); Apr (0.83); Jul (0.69); Oct (0.79). A negative bias (undersimulation) exists in the reanalysis wind speeds for January through July, but is typically 3ms-1 or less in magnitude. Overall, the magnitude of the wind vector is undersimulated approximately 74% of the time in the cold season months and 85% of the time July, but only about half of the time in October. Wind direction biases in the model are generally small (10-20 degrees), but they are generally in the leftward-turning direction in all months. We also synthesized NARR atmospheric output into a composite analysis of the synoptic conditions that are present when the reanalysis model fails in its simulations of Arctic cloud fractions, and similarly, those conditions present when the model simulates accurate cloud fractions. Cold season errors were highest when high pressure was located north of Barrow favoring anomalous winds and longer fetches from the northeast. In addition, larger cloud fraction biases were found on days with relatively calm winds (2-5 m/s). The most pronounced oversimulation biases associated with poorly simulated clouds occur during conditions with very low cloud-base heights (< 50 m). In contrast, the model appears more adept at capturing cloudless conditions in the spring than the winter with oversimulations occurring just 5% of the time in spring compared to 20% in the winter months. During the warm season, low level clouds are present in 32% of the time with onshore flow and less than half this frequent in offshore wind conditions. Composite sea level pressure fields indicate that clear sky conditions typically result when high pressure is centered at or near Barrow, AK. Overcast days are associated with generally lower sea level pressures near the North Slope and onshore flow from the NW in most months. Warm season errors were highest when high pressure was persistent to the north of Barrow, AK. This synoptic situation results in onshore flow for the North Slope with persistent winds from the east and northeast. In these situations, the predominant climatological synoptic situation, the NARR model under-simulates summer clouds on the North Slope. In general, the NARR often fails to capture clouds in the lowest 200 meters of the atmosphere. We conclude that the cloud model parameterization fails to cature boundary layer clouds like Arctic stratus and fog, which are observed in 65% of the undersimulations. These NARR undersimulations occur most often during onshore flow environments, such as when high pressure is located north of Barrow and the prevailing winds are from the northeast. In these cases, the airflow is along a fetch of scattered sea ice and open ocean (ice concentrations between 0 and 100%). NARR treats sea ice as a binary function. Grid cells are either considered a slap of ice cover, or totally open ocean. We note that implementing provisions for partial sea ice concentrations in the reanalysis model may help in more accurately depicting surface moisture fluxes and associated model-derived low cloud amounts.

  3. Computing for Finance

    ScienceCinema (OSTI)

    None

    2011-10-06

    The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing ? from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with "Seti@Home". Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zrich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

  4. Computing for Finance

    ScienceCinema (OSTI)

    None

    2011-10-06

    The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing ? from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with "Seti@Home". Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

  5. Computing for Finance

    SciTech Connect (OSTI)

    2010-03-24

    The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with "Seti@Home". Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.