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Towards an Improved Understanding of...

Jiang, Zhiyuan.

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Towards an Improved Understanding of Ice Processes in Clouds and Precipitation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Towards an Improved Understanding of Ice Processes in Clouds and Precipitation./
作者:	Jiang, Zhiyuan.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	174 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:	Dissertations Abstracts International80-10B.
標題:	Meteorology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13871842
ISBN:	9781392039359

Towards an Improved Understanding of Ice Processes in Clouds and Precipitation.
Jiang, Zhiyuan.

Towards an Improved Understanding of Ice Processes in Clouds and Precipitation. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 174 p.

Source: Dissertations Abstracts International, Volume: 80-10, Section: B.

Thesis (Ph.D.)--The Pennsylvania State University, 2018.

This item must not be sold to any third party vendors.

Ice processes play an important role in both climate (e.g., Earth's energy budget) and severe weather events (e.g., snowstorms and hailstorms), yet details in our understanding of them still need to be improved in order to improve their representation in numerical models and to better interpret measurements from advanced remote sensing instruments. This dissertation aims to improve our understanding of ice processes in clouds, either by simulating remote sensing observations of ice particles (e.g., radar scattering characteristics of ice particles at multiple frequencies), or by retrieving physical characteristics of ice particles from measurements. The study started by completing a scattering database of various ice particles at multiple radar frequencies. Scattering properties of ice particles are necessary in order to interpret the remote sensing observations. A comprehensive scattering library of ice particle scattering properties at multiple radar frequencies was produced including vapor-grown pristine ice of known habits (e.g., dendrites, plates and columns of known characteristics), and also collision-grown ice particles such as graupel and aggregates. However, hailstones are not included in the scattering library due to the lack of morphology. Their scattering properties using detailed shapes of real 3D hailstones collected during recent field campaigns were computed accurately and compared to the results of simplified shapes (i.e., spheroids). The results show that their scattering properties are different from the simplified spheroid counterparts often employed to model their scattering behavior, which explains why spheroids cannot reproduce the radar signatures of hailstones in many observed cases. In addition to hailstones, the shape of aggregates is difficult to characterize as well. Aggregates are so delicate that their shapes have to be measured while falling. In this work, an algorithm is developed to retrieve the bounding ellipsoidal shapes and their orientations of ice aggregates from multiple projections/images, adding additional complexities compared to the oft-assumed, but unsatisfactory and inaccurate, spheroidal shape. The aggregate shape distribution retrieved from Multi-Angle Snowflake Camera images can be used in future developments of ice particle aggregate microphysical schemes. The more complex 3D shapes retrieved from real ice particles raised questions about the practice of using single 2D projections of these complex-shaped ice particles for the evaluation of 3D ice particle physical properties from model output and/or retrieved from remote sensing measurements. A theoretical method to convert the bulk physical properties of 3D ice particles from numerical model outputs to the properties of particle 2D projections is developed, which can be used to compare model outputs directly with in-situ image measurements of ice particles.

ISBN: 9781392039359Subjects--Topical Terms:

542822
Meteorology.

Towards an Improved Understanding of Ice Processes in Clouds and Precipitation.
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520 $a Ice processes play an important role in both climate (e.g., Earth's energy budget) and severe weather events (e.g., snowstorms and hailstorms), yet details in our understanding of them still need to be improved in order to improve their representation in numerical models and to better interpret measurements from advanced remote sensing instruments. This dissertation aims to improve our understanding of ice processes in clouds, either by simulating remote sensing observations of ice particles (e.g., radar scattering characteristics of ice particles at multiple frequencies), or by retrieving physical characteristics of ice particles from measurements. The study started by completing a scattering database of various ice particles at multiple radar frequencies. Scattering properties of ice particles are necessary in order to interpret the remote sensing observations. A comprehensive scattering library of ice particle scattering properties at multiple radar frequencies was produced including vapor-grown pristine ice of known habits (e.g., dendrites, plates and columns of known characteristics), and also collision-grown ice particles such as graupel and aggregates. However, hailstones are not included in the scattering library due to the lack of morphology. Their scattering properties using detailed shapes of real 3D hailstones collected during recent field campaigns were computed accurately and compared to the results of simplified shapes (i.e., spheroids). The results show that their scattering properties are different from the simplified spheroid counterparts often employed to model their scattering behavior, which explains why spheroids cannot reproduce the radar signatures of hailstones in many observed cases. In addition to hailstones, the shape of aggregates is difficult to characterize as well. Aggregates are so delicate that their shapes have to be measured while falling. In this work, an algorithm is developed to retrieve the bounding ellipsoidal shapes and their orientations of ice aggregates from multiple projections/images, adding additional complexities compared to the oft-assumed, but unsatisfactory and inaccurate, spheroidal shape. The aggregate shape distribution retrieved from Multi-Angle Snowflake Camera images can be used in future developments of ice particle aggregate microphysical schemes. The more complex 3D shapes retrieved from real ice particles raised questions about the practice of using single 2D projections of these complex-shaped ice particles for the evaluation of 3D ice particle physical properties from model output and/or retrieved from remote sensing measurements. A theoretical method to convert the bulk physical properties of 3D ice particles from numerical model outputs to the properties of particle 2D projections is developed, which can be used to compare model outputs directly with in-situ image measurements of ice particles.
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