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Numerical simulations on the redistr...

Chen, Jen-Ping,

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Numerical simulations on the redistribution of atmospheric trace chemicals through cloud processes /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Numerical simulations on the redistribution of atmospheric trace chemicals through cloud processes // Jen-Ping Chen.
Author:	Chen, Jen-Ping,
Description:	1 electronic resource (360 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 54-10, Section: B.
Contained By:	Dissertations Abstracts International54-10B.
Subject:	Atmosphere. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9311607
ISBN:	9798641027425

Numerical simulations on the redistribution of atmospheric trace chemicals through cloud processes /
Chen, Jen-Ping,

Numerical simulations on the redistribution of atmospheric trace chemicals through cloud processes /Jen-Ping Chen. - 1 electronic resource (360 pages)

Source: Dissertations Abstracts International, Volume: 54-10, Section: B.

The redistribution of atmospheric trace substances through cloud processes is investigated using a detailed microphysical and chemical cloud model. A multi-component categorization scheme is used in the model to group cloud particles into different bins according to their various properties. Cloud drops are categorized in both their water mass and solute mass components. An extra "shape" component is included in the ice-phase particle framework to describe the distribution of ice-phase particles. Special efforts are paid to develop the theory and parameterization for the change of the growth habits for ice particles. In dealing with a model that inevitably has a large dimension, a hybrid bin-method is applied so that it can maintain the conservation of all properties and, at the same time, perform fast and accurate calculations for transferring various properties between categories in the multi-component systems. With a minimum of parameterization, this model is capable of simulating detailed microphysical and chemical processes that occurred during cloud and precipitation formations. Using the multi-component model, it is shown that the drop number concentration is a function of both the water mass and the solute mass in the drops, a phenomenon that cannot be resolved by conventional cloud models. Applying a full set of liquid- and ice-phase microphysics, it is also shown that the number concentration of ice particles is indirectly controlled by the number concentration of cloud condensation nuclei. Bulkwater models that can not treat the in-cloud supersaturation are not able to properly simulate such processes. The concept of the relative removal efficiency was introduced and tested in a simple particle model in the earlier stage of the study. An extended test on the relative removal efficiencies was done by simulating a wintertime, orographic cloud in a two-dimensional, steady-state model. Satisfactory results for both the microphysical and chemical behavior of the cloud are produced in the simulation. It is shown that the redistribution of atmospheric trace substances is controlled by their microphysical pathways.

English

ISBN: 9798641027425Subjects--Topical Terms:

542821
Atmosphere.
Subjects--Index Terms:

precipitation

Numerical simulations on the redistribution of atmospheric trace chemicals through cloud processes /
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100 1 $a Chen, Jen-Ping, $e author. $3 3765933
245 1 0 $a Numerical simulations on the redistribution of atmospheric trace chemicals through cloud processes / $c Jen-Ping Chen.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 1992
300 $a 1 electronic resource (360 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
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500 $a Source: Dissertations Abstracts International, Volume: 54-10, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisors: Lamb, Dennis.
502 $b Ph.D. $c The Pennsylvania State University $d 1992.
520 $a The redistribution of atmospheric trace substances through cloud processes is investigated using a detailed microphysical and chemical cloud model. A multi-component categorization scheme is used in the model to group cloud particles into different bins according to their various properties. Cloud drops are categorized in both their water mass and solute mass components. An extra "shape" component is included in the ice-phase particle framework to describe the distribution of ice-phase particles. Special efforts are paid to develop the theory and parameterization for the change of the growth habits for ice particles. In dealing with a model that inevitably has a large dimension, a hybrid bin-method is applied so that it can maintain the conservation of all properties and, at the same time, perform fast and accurate calculations for transferring various properties between categories in the multi-component systems. With a minimum of parameterization, this model is capable of simulating detailed microphysical and chemical processes that occurred during cloud and precipitation formations. Using the multi-component model, it is shown that the drop number concentration is a function of both the water mass and the solute mass in the drops, a phenomenon that cannot be resolved by conventional cloud models. Applying a full set of liquid- and ice-phase microphysics, it is also shown that the number concentration of ice particles is indirectly controlled by the number concentration of cloud condensation nuclei. Bulkwater models that can not treat the in-cloud supersaturation are not able to properly simulate such processes. The concept of the relative removal efficiency was introduced and tested in a simple particle model in the earlier stage of the study. An extended test on the relative removal efficiencies was done by simulating a wintertime, orographic cloud in a two-dimensional, steady-state model. Satisfactory results for both the microphysical and chemical behavior of the cloud are produced in the simulation. It is shown that the redistribution of atmospheric trace substances is controlled by their microphysical pathways.
546 $a English
590 $a School code: 0176
650 4 $a Atmosphere. $3 542821
653 $a precipitation
690 $a 0725
710 2 $a The Pennsylvania State University. $e degree granting institution. $3 3765934
720 1 $a Lamb, Dennis $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 54-10B.
790 $a 0176
791 $a Ph.D.
792 $a 1992
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9311607