Active research topics in radar meteorology concern classification algorithms, in order to distinguish a larger number of target classes, as well as quantitative precipitation estimation, in order to invert models to obtain important geophysical parameters from observations. This project will investigate the full use of all observed polarimetric variables to accomplish these goals.

Radar polarimetry has the task to provide radar meteorology with the most meaningful quantities for optimal hydrometeor classification and quantitative precipitation estimation. The variables in use should have, ideally, rich physical meaning, that is, it should be possible to relate their values, as precisely and linearly as possible, to some geophysical feature of the illuminated target. The process of searching the optimal set of polarimetric variables has not ended yet. In this project you will actively engage in this pursuit.

As such, this work may include the definition of new quantities (i.e. new combinations of observed variables). New definitions are highly needed since existing operational variables do not generally capture all the degrees of freedom contained in the polarised radar measurements. Also, new variables might highlight physical properties of the target hydrometeors in unique ways, thus rendering classification and/or model inversion more effective.

This project may also include the development of more complex signal processing to take full advantage of physically meaningful polarimetric signals. The application of target decomposition theorems or of unitary transformations, as well as the evaluation of the depolarization response (Galetti, 2009) rank among these possibilities.

Objectives

This project will significantly contribute to the field of radar polarimetry, with specifc applications to polarimetric classification of weather radar targets. In this project, you will work with world leading scientists at the Univeristy of Leeds and NCAS to:

Become an expert in making and analysing dual-polarisation Doppler radar observations.
Determine and evaluate the use of polarimetric parameters to quantify hydrometer size, concentration, phase, shape, and orientation.
Use polarimetric radar observations to improve parameterizations of precipitation in forecast models.
One unique aspect of this project is that you will be trained to go into the field and make observations with the new NCAS mobile dual-polarisation Doppler radar. The observations you make with this instrument will provide the basis of your exploration in the use of polarimetric radar observations, though the total fieldwork component of the project may vary depending on the role of the radar in upcoming field campaigns and your interest.

Observational analysis may also include exploring observations from the recently upgraded UK weather radar network and applying techniques learned from the use of the NCAS Mobile dual-polarisation Doppler radar. This extension of the project would specifically examine the use of polarimetric variables from a network radars as has been done with American WSR-88D network in Homeyer et al. (2014).

Potential for high impact outcome

Polarimetry is currently becoming an operational feature of weather radar systems around the world. Such a choice has been motivated by the capability of polarimetric variables to distinguish different hydrometeor types and to improve the accuracy of quantitative precipitation estimation. These technologies have attained a degree of maturity such that major investments were undertaken by many national governments (notably the US, UK and Europe) for the implementation of polarimetric upgrades of weather radar networks. Yet, much work remains to fully incorporate all of the new information these observations provide into operational observation and forecast systems.

Thus, we anticipate the project generating several papers with at least one being suitable for submission to a high impact journal due to the relevancy to radar polarimetry for greatly improving operational radar meteorology and forecasting.

This work will also have the possibility of impacting society. The new observational abilities being investigated will eventually lead to better information being provided directly to forecasting systems from operational radar networks. This will directly result in more accurate predictions and as well as lead to improved model parameterizations.

Training

You will work directly under the supervision of Dr. Ryan R. Neely III and Profs . Alan Blyth and Chris Collier within ICAS and the NCAS Weather directorate.You will become a member of the University of Leeds Remote Sensing Group and benefit from interactions with other staff and students within NCAS and SEEwho have a range of interests and expertise.

This project will equip you with the necessary expertise to become a leader in the next generation of atmospheric scientists, ready to carry out your own programme of innovative scientific research. These skills will be developed by a mixture of hands on experience, attending external training courses, and taking part in the Leeds – York NERC doctoral training partnership programme. This includes access to a broad spectrum of training workshops put on by the Faculty that consist of a range of extensive training workshops that will help you manage your degree and prepare for your viva (http://www.emeskillstraining.leeds.ac.uk/).

Specifically, this project will provide a high level of specialist scientific training in: (i) State-of-the-art analysis and application polarmetric Doppler radar observations; (ii) radiative transfer (with an emphasis on polarization and scattering processes); (iii) comparison of radar derived geophysical parameters to forecast models; (iv) planning and executing measurement campaigns.

You will also have the opportunity to present research results at national and international conferences, and you will benefit from established collaborations with world-leading scientists within NCAS, the Met Office,NCAR and NOAA.

Requirements

UK or EU citizenship. A good first degree (1 or good 2-1), or a good Masters degree in a physical or mathematical discipline, such as mathematics, physics, geophysics, engineering or meteorology is required. Experience in programming (eg. Matlab, IDL, R…) and fieldwork is of advantage.

Contact Information

Contact is strongly encourage before application so that we may discuss your interests and project specifics. Help with the application process may also be provided. Enquires should be made by contacting Dr. Ryan Neely, Lecturer of Observational Atmospheric Science (R.Neely<στο>leeds.ac.uk). …