|From||Sue Grimmond <email@example.com>|
|To||"firstname.lastname@example.org" <email@example.com>, "firstname.lastname@example.org" <email@example.com>|
|Cc||Stefan Thor Smith <firstname.lastname@example.org>|
|Date||Tue, 31 Mar 2015 15:50:54 +0000|
Optimising future observing networks for the evolving urban landscape (NERC/University Of Reading funded)
Supervised by Prof Sue Grimmond (University of Reading), Humphrey Lean, Cristina Charlton-Perez, Sue Ballard (Met Office)
Urban areas will soon be simulated in remarkable detail in both climate and weather models as these models rapidly move toward resolutions of 10's of kilometres and 100's of metres, respectively. This move begs for the use of data gathered from densely populated, high-resolution observation networks both for verification and data assimilation purposes. Novel data types such as those observed using ceilometers are being evaluated for use in numerical weather prediction. This project is motivated by the question what is the appropriate density of a network of ceilometers for measuring the important meteorological characteristics of urban areas? Modellers are often asked this challenging question. The answer will depend on factors including the large-scale geography of a region, the size of urban areas and their location within the landscape. Ceilometer data from the rural Met Office network and the London Urban Meteorological Observatory network will be analysed and compared to forecasts of cloud, aerosol, fog and boundary layer height from the 1.5 km Met Office’s high-resolution operational model and from an experimental configuration of the Met Office’s weather forecast model over London that is being run routinely with a view to improving fog and temperature forecasts.
Reviews will be done on an ongoing basis until the positions are filled. But for the best consideration please have your applications submitted by April 15th.
Initial applications should include a cover letter, curriculum vitae and the names of two academic references. These should be emailed to email@example.com
Two EPSRC funded: Multi-scale anthropogenic heat flux modelling: current and future energy systems
Two full-time PhD studentships are available at the University of Reading, based on anthropogenic heat flux modelling. Both will be jointly supervised by Prof. Sue Grimmond (School of Mathematical and Physical Sciences) and Dr. Stefan Smith (School of Construction Management and Engineering).
The two PhD projects aim to improve understanding of the impact of energy systems on local urban climate and the feedback of energy systems impact on spatial and temporal variations in urban climate. The projects are embedded in understanding the interaction between engineered energy systems and bio-physical systems.
The two studentships are titled:
1) Improving the processes in anthropogenic heat flux models that are integrated into urban climate models of different scales
The aim is to develop a generalized model with processes appropriate for integration into different urban land surface models that can be embedded within larger scale models and run at different scales (from city to global) to assess city, regional, and global scale implications of changes in the energy infrastructure in cities. This will draw on agent-based modelling, undertaken at the micro-scale, in order to scale-up behavioural characteristics for building energy use, transportation and other human activities from a neighborhood/land-use up to an entire city. Such an approach will allow new energy and transport systems to be included, along with changes in human behaviours and activities, and their impacts evaluated.
2) Static to dynamic data mining to improve future predictions of anthropogenic heat flux
Current modelling of anthropogenic heat fluxes are based on data sets that are representative of the past, rather than the current or future state of city energy systems. However, many of these data sets are regularly updated making it possible to model representations of energy systems to better capture the influence of those systems on heat fluxes. As an example, satellite data can be used to highlight energy `hotspots’ that can be related to anthropogenic activity at a given time and location. Incorporating data sets such as these into the modelling process can give greater accuracy in relating energy system behaviour to anthropogenic heat flux. Through incorporating dynamic data mining into the modelling process, early trends in behaviour change and system changes can be detected and investigated for better projection of current and future energy use.
For each project the applicant will have an excellent honours degree (at least 2.i or equivalent) in a scientific, engineering or relevant discipline and will have or be able to develop necessary programming skills for modelling, and data mining. These studentships are funded through the EPSRC and candidates must, therefore meet their eligibility requirements (http://www.epsrc.ac.uk/skills/students/help/eligibility/).
Fixed-term: Both studentships are fully funded and run for 3.5 years.
Reviews will be done on an ongoing basis until the positions are filled. But for the best consideration please have your applications submitted by April 20th.
Prof Sue Grimmond
Department of Meteorology, University of Reading,
Earley Gate, PO Box 243, Reading, RG6 6BB, UK
T:+44 118 378 6248
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