YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Journal of the Atmospheric Sciences
    • View Item
    •   YE&T Library
    • AMS
    • Journal of the Atmospheric Sciences
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Microphysical and Large-Scale Dependencies of Temporal Rainfall Variability over a Tropical Ocean

    Source: Journal of the Atmospheric Sciences:;1999:;Volume( 056 ):;issue: 005::page 724
    Author:
    Tsintikidis, Dimitris
    ,
    Georgakakos, Konstantine P.
    DOI: 10.1175/1520-0469(1999)056<0724:MALSDO>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: The focus of this paper is the elucidation of the physical origins of the observed extreme rainfall variability over tropical oceans. A simple statistical?dynamical model, suitable for use in repetitive Monte Carlo experiments, is formulated as a diagnostic tool for this purpose. The model is based on three partial differential equations that describe airmass, water substance, and vertical momentum conservation in a column of air extending from the ocean surface to the top of the storm clouds. Tropospheric conditions are specified for the model state variables (such as updraft?downdraft velocity, precipitation water and cloud content, or saturation vapor deficit) in accordance with past observations in oceanic convection, to allow for vertical integration of the model equations and the formulation of a computationally efficient diagnostic tool. Large-scale forcing is represented by stochastic processes with temporal structure and parameters estimated from observed large-scale data. This model formulation allows for sensitivity studies of surface rainfall temporal variability as it is affected by microphysical processes and variability in large-scale forcing. Dependence of the results on model-simplifying assumptions is quantified. Data from the Tropical Ocean Global Atmosphere Coupled Ocean?Atmosphere Response Experiment are used to validate the formulation statistically and to produce forcing parameters for the sensitivity studies. On the basis of Monte Carlo simulations that resulted in the generation of 10-min rainfall rates averaged over 4 km ? 4 km, it is found that (a) the probability distribution function of model-generated rainfall resembles that of observed rainfall obtained by rain gauges and radar; (b) the power spectra of the model-generated rain time series, while reproducing the power-law character of the observed spectra for high rain rates, have generally steeper slopes than those of the radar-observed ones; (c) the character and magnitude of the model-generated rainfall variability are substantially influenced by the model microphysical parameterization and, to a lesser extent, by the shape of the vertical profiles of the state variables; and (d) while the probability of local rain is substantially influenced by both thermal buoyancy and water vapor availability, the exceedance probability of high rain rates (>10 mm h?1) is much more sensitive to changes in the former than in the latter large-scale forcing. The quantitative results of this work may be used to establish links between deterministic models of the mesoscale and synoptic scale with statistical descriptions of the temporal variability of local tropical oceanic rainfall. In addition, they may be used to quantify the influence of measurement error in large-scale forcing and cloud-scale observations on the accuracy of local rainfall variability inferences, important for hydrologic studies.
    • Download: (660.7Kb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Microphysical and Large-Scale Dependencies of Temporal Rainfall Variability over a Tropical Ocean

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4158714
    Collections
    • Journal of the Atmospheric Sciences

    Show full item record

    contributor authorTsintikidis, Dimitris
    contributor authorGeorgakakos, Konstantine P.
    date accessioned2017-06-09T14:35:18Z
    date available2017-06-09T14:35:18Z
    date copyright1999/03/01
    date issued1999
    identifier issn0022-4928
    identifier otherams-22281.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4158714
    description abstractThe focus of this paper is the elucidation of the physical origins of the observed extreme rainfall variability over tropical oceans. A simple statistical?dynamical model, suitable for use in repetitive Monte Carlo experiments, is formulated as a diagnostic tool for this purpose. The model is based on three partial differential equations that describe airmass, water substance, and vertical momentum conservation in a column of air extending from the ocean surface to the top of the storm clouds. Tropospheric conditions are specified for the model state variables (such as updraft?downdraft velocity, precipitation water and cloud content, or saturation vapor deficit) in accordance with past observations in oceanic convection, to allow for vertical integration of the model equations and the formulation of a computationally efficient diagnostic tool. Large-scale forcing is represented by stochastic processes with temporal structure and parameters estimated from observed large-scale data. This model formulation allows for sensitivity studies of surface rainfall temporal variability as it is affected by microphysical processes and variability in large-scale forcing. Dependence of the results on model-simplifying assumptions is quantified. Data from the Tropical Ocean Global Atmosphere Coupled Ocean?Atmosphere Response Experiment are used to validate the formulation statistically and to produce forcing parameters for the sensitivity studies. On the basis of Monte Carlo simulations that resulted in the generation of 10-min rainfall rates averaged over 4 km ? 4 km, it is found that (a) the probability distribution function of model-generated rainfall resembles that of observed rainfall obtained by rain gauges and radar; (b) the power spectra of the model-generated rain time series, while reproducing the power-law character of the observed spectra for high rain rates, have generally steeper slopes than those of the radar-observed ones; (c) the character and magnitude of the model-generated rainfall variability are substantially influenced by the model microphysical parameterization and, to a lesser extent, by the shape of the vertical profiles of the state variables; and (d) while the probability of local rain is substantially influenced by both thermal buoyancy and water vapor availability, the exceedance probability of high rain rates (>10 mm h?1) is much more sensitive to changes in the former than in the latter large-scale forcing. The quantitative results of this work may be used to establish links between deterministic models of the mesoscale and synoptic scale with statistical descriptions of the temporal variability of local tropical oceanic rainfall. In addition, they may be used to quantify the influence of measurement error in large-scale forcing and cloud-scale observations on the accuracy of local rainfall variability inferences, important for hydrologic studies.
    publisherAmerican Meteorological Society
    titleMicrophysical and Large-Scale Dependencies of Temporal Rainfall Variability over a Tropical Ocean
    typeJournal Paper
    journal volume56
    journal issue5
    journal titleJournal of the Atmospheric Sciences
    identifier doi10.1175/1520-0469(1999)056<0724:MALSDO>2.0.CO;2
    journal fristpage724
    journal lastpage748
    treeJournal of the Atmospheric Sciences:;1999:;Volume( 056 ):;issue: 005
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian