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Thesis H/F: microphysical processes in ice clouds and crystal morphology

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Français - Anglais

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General information

Reference : UMR6016-ALFSCH-001
Workplace : AUBIERE
Date of publication : Friday, October 25, 2019
Scientific Responsible name : Prof. Alfons Schwarzenboeck
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 December 2019
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

Physical properties (dimension, shape, phase, concentration,…) of ice crystals are key parameters for a better representation of the ice phase in atmospheric models (cloud process models, mesoscale models, GCM) and in radiative transfer calculations. Improved understanding of ice microphysics and more sophisticated cloud model microphysical parametrizations of the onset and development of the ice phase will also help validating retrievals from cloud remote sensing instruments (cloud radars and radiometers on aircraft and satellites). Also research progress with respect to cloud ice phase is particularly needed for the aviation industry. For example, high concentrations of small ice particles have been recognized as a threat to commercial aviation, causing hazardous icing conditions for aircraft engines and Pitot probes.
Technological developments improve continuously our instrumental means for in-situ investigations of microphysical properties of ice hydrometeors (range of small ice crystals to largest rimed particles and snowflakes). In the framework of past and current national and international projects (e.g. HAIC (FP7) and ICE-GENESIS (Horizon 2020) both led by Airbus Industry, ACLOUD and MOZAIC projects in Arctic clouds led by the German Arctic Research Center AWI, and e.g. the French national project ANR EXAEDRE dedicated to better understanding of cloud electrical phenomena), the characterization of the crystal geometry, fall speed, mass and density of individual hydrometeors is of particular interest. Within the above projects (including numerous past and near future worldwide measurement campaigns in 2014-2021) the LaMP research laboratory operated the French Airborne Measurement Platform PMA during above mentioned campaigns on various research aircraft, thereby collecting representative sets of high quality cloud measurements. The PMA consists of a suite of modern cloud instruments to investigate ice particle properties. Amongst all PMA instruments, cloud particle imaging probes (optical array or CCD-based probes) produce detailed 2D shadow images of individual ice particles. From these images, valuable information related to the microphysical processes governing the growth of these ice particles (aggregation, riming, water vapor deposition) can be inferred.
Past PhD thesis at LaMP created considerable insights in ice microphysics from Polar Regions to the Tropics within these research projects. Within the new thesis we want to emphasize the morphological analysis of ice crystals, which has not been the primary focus of past work. Based on existing software of automatic ice crystal classification at the laboratory, we wish to exploit and then adapt these existing tools retrieving geometric information on an individual crystal basis with subsequent shape classification for some representative datasets. Further development is scheduled to create a newer automatic classification technique for 2D images.
The main challenge within the thesis work is to extract reliable information from the huge amount of recorded images for different instruments (order of magnitude of 10 - 10 000 images per second of flight). In more detail, the work will include:
1. Development of advanced data processing algorithms for the retrieval of morphological properties and their statistics (shape, size, fractal dimension, deformation, growth pattern, …) from readily available datasets (MEGHA-TROPIQUES, HYMEX, HAIC, EXAEDRE), as well as the collection of data through the participation to ground and/or airborne field campaigns planned in winter 2019/2020 and 2020/2021 (ICE GENESIS).
2. Analysis of retrieved hydrometeors' properties in order to quantify the variability in space and time of underlying ice growth processes in various cloud conditions. This research should significantly contribute to the puzzling problem of better understanding the interaction between microphysics, dynamics, and thermodynamics in clouds.
The work will be closely followed and supported by all three supervisors.

Work Context

Physical properties (dimension, shape, phase, concentration,…) of ice crystals are key parameters for a better representation of the ice phase in atmospheric models (cloud process models, mesoscale models, GCM) and in radiative transfer calculations. Improved understanding of ice microphysics and more sophisticated cloud model microphysical parametrizations of the onset and development of the ice phase will also help validating retrievals from cloud remote sensing instruments (cloud radars and radiometers on aircraft and satellites). Also research progress with respect to cloud ice phase is particularly needed for the aviation industry. For example, high concentrations of small ice particles have been recognized as a threat to commercial aviation, causing hazardous icing conditions for aircraft engines and Pitot probes.
Technological developments improve continuously our instrumental means for in-situ investigations of microphysical properties of ice hydrometeors (range of small ice crystals to largest rimed particles and snowflakes). In the framework of past and current national and international projects (e.g. HAIC (FP7) and ICE-GENESIS (Horizon 2020) both led by Airbus Industry, ACLOUD and MOZAIC projects in Arctic clouds led by the German Arctic Research Center AWI, and e.g. the French national project ANR EXAEDRE dedicated to better understanding of cloud electrical phenomena), the characterization of the crystal geometry, fall speed, mass and density of individual hydrometeors is of particular interest. Within the above projects (including numerous past and near future worldwide measurement campaigns in 2014-2021) the LaMP research laboratory operated the French Airborne Measurement Platform PMA during above mentioned campaigns on various research aircraft, thereby collecting representative sets of high quality cloud measurements. The PMA consists of a suite of modern cloud instruments to investigate ice particle properties. Amongst all PMA instruments, cloud particle imaging probes (optical array or CCD-based probes) produce detailed 2D shadow images of individual ice particles. From these images, valuable information related to the microphysical processes governing the growth of these ice particles (aggregation, riming, water vapor deposition) can be inferred.
Past PhD thesis at LaMP created considerable insights in ice microphysics from Polar Regions to the Tropics within these research projects. Within the new thesis we want to emphasize the morphological analysis of ice crystals, which has not been the primary focus of past work. Based on existing software of automatic ice crystal classification at the laboratory, we wish to exploit and then adapt these existing tools retrieving geometric information on an individual crystal basis with subsequent shape classification for some representative datasets. Further development is scheduled to create a newer automatic classification technique for 2D images.
The main challenge within the thesis work is to extract reliable information from the huge amount of recorded images for different instruments (order of magnitude of 10 - 10 000 images per second of flight). In more detail, the work will include:
1. Development of advanced data processing algorithms for the retrieval of morphological properties and their statistics (shape, size, fractal dimension, deformation, growth pattern, …) from readily available datasets (MEGHA-TROPIQUES, HYMEX, HAIC, EXAEDRE), as well as the collection of data through the participation to ground and/or airborne field campaigns planned in winter 2019/2020 and 2020/2021 (ICE GENESIS).
2. Analysis of retrieved hydrometeors' properties in order to quantify the variability in space and time of underlying ice growth processes in various cloud conditions. This research should significantly contribute to the puzzling problem of better understanding the interaction between microphysics, dynamics, and thermodynamics in clouds.
The work will be closely followed and supported by all three supervisors.

Additional Information

We are looking for a motivated PhD student to investigate above scientific questions. The candidate should hold a Master of Science or equivalent in a field relevant to the proposed research field (e.g. Environmental Sciences, Applied Mathematics, or Statistics). Good working skills on either image analysis, advanced data processing (e.g. neural network, clustering) or statistics applied to experimental data will be an asset for this position. We expect the candidate to be proficient in a programming language (Python, Matlab, etc…). Proficiency in English is a prerequisite.

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