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Linking Remote Sensing and In-Situ Data of Cloud Properties

Keppas, Stavros

[Thesis]. Manchester, UK: The University of Manchester; 2019.

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Abstract

Clouds play a major role in many earth-atmosphere system processes, such as precipitation processes and radiative transfer affecting the weather and the climate. Although these processes are included in atmospheric numerical models, they still remain uncertain. This thesis focuses on the comprehensive microphysical analysis of a warm front of a wide low pressure system over the north Atlantic ocean, which affected the United Kingdom on 21 January 2009. For this analysis, airborne and ground based measurements are compared in order to investigate and understand microphysical properties and structures of the clouds. During the investigation of the warm front, a warm conveyor belt was always activated transporting humid air aloft and causing the formation of massive stratiform clouds with embedded convective elements, which are called “generating cells”. Such cells consist of a high reflectivity factor (ZH) core with rimed crystals and high differential reflectivity (ZDR) boundaries with pristine planar crystals. Expanding on the effect and the evolution of these convective features, which were entering the warm conveyor belt dominated by strong and sheared westerlies, they were transformed into two slanted fall streaks of different polarimetric and microphysical characteristics. The microphysical processes within these structures together with the presence of strong winds along the profile of the atmosphere can affect the time and the place of the occurrence of surface precipitation. Further analysis of the warm front focused on the processes occurring at the upper regions of the clouds and within the warm conveyor belt. For first time, we observed high concentrations of an ice particle with distinctive shape referred to as “ice-lolly”, the formation of which is explained. These particles can potentially play an important role in the lifetime of the clouds and the surface precipitation, being produced due to the interaction between the warm conveyor belt and the ice multiplication mechanism. The latter part of the present thesis focuses on the evaluation of the NCAR’s Hydrometeor Classification Algorithm (HCA) for S-band radar suggesting a validation methodology based on in-situ aircraft measurements. Alongside 2DS and CIP-100 probe images, we also used calculated parameters such as mean particle size measurements, concentration of particles of sizes <1000μm and >1000μm, Liquid Water Content (LWC), weighted shape factor, weighted area ratio and weighted transparency retrievals. Although they provided useful information about the ice particles in the clouds, further work could improve the efficiency of using such parameters. The HCA results seem to generally agree with the in-situ observations. However, the presence of liquid water close to the melting layer may be problematic for hydrometeor classification.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor Of Philosophy
Degree programme:
PhD Atmospheric Sciences
Publication date:
Location:
Manchester, UK
Total pages:
206
Abstract:
Clouds play a major role in many earth-atmosphere system processes, such as precipitation processes and radiative transfer affecting the weather and the climate. Although these processes are included in atmospheric numerical models, they still remain uncertain. This thesis focuses on the comprehensive microphysical analysis of a warm front of a wide low pressure system over the north Atlantic ocean, which affected the United Kingdom on 21 January 2009. For this analysis, airborne and ground based measurements are compared in order to investigate and understand microphysical properties and structures of the clouds. During the investigation of the warm front, a warm conveyor belt was always activated transporting humid air aloft and causing the formation of massive stratiform clouds with embedded convective elements, which are called “generating cells”. Such cells consist of a high reflectivity factor (ZH) core with rimed crystals and high differential reflectivity (ZDR) boundaries with pristine planar crystals. Expanding on the effect and the evolution of these convective features, which were entering the warm conveyor belt dominated by strong and sheared westerlies, they were transformed into two slanted fall streaks of different polarimetric and microphysical characteristics. The microphysical processes within these structures together with the presence of strong winds along the profile of the atmosphere can affect the time and the place of the occurrence of surface precipitation. Further analysis of the warm front focused on the processes occurring at the upper regions of the clouds and within the warm conveyor belt. For first time, we observed high concentrations of an ice particle with distinctive shape referred to as “ice-lolly”, the formation of which is explained. These particles can potentially play an important role in the lifetime of the clouds and the surface precipitation, being produced due to the interaction between the warm conveyor belt and the ice multiplication mechanism. The latter part of the present thesis focuses on the evaluation of the NCAR’s Hydrometeor Classification Algorithm (HCA) for S-band radar suggesting a validation methodology based on in-situ aircraft measurements. Alongside 2DS and CIP-100 probe images, we also used calculated parameters such as mean particle size measurements, concentration of particles of sizes <1000μm and >1000μm, Liquid Water Content (LWC), weighted shape factor, weighted area ratio and weighted transparency retrievals. Although they provided useful information about the ice particles in the clouds, further work could improve the efficiency of using such parameters. The HCA results seem to generally agree with the in-situ observations. However, the presence of liquid water close to the melting layer may be problematic for hydrometeor classification.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:320192
Created by:
Keppas, Stavros
Created:
17th July, 2019, 11:06:49
Last modified by:
Keppas, Stavros
Last modified:
14th August, 2019, 10:40:28

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