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Today's Topics:
1. Job opening Flood Modeler, RMS, London (Arno Hilberts)
2. NERC PhD Case Studentship: Surface fluxes, temperatures and
boundary layer evolution at the building greyzone in London
(Sue Grimmond)
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Message: 1
Date: Fri, 18 Dec 2015 14:08:29 +0000
From: Arno Hilberts <Arno.Hilberts@rms.com>
To: "met-jobs@lists.reading.ac.uk" <met-jobs@lists.reading.ac.uk>
Subject: [Met-jobs] Job opening Flood Modeler, RMS, London
Message-ID:
<DM2PR06MB672E468EC939272CC0D22BFFAE10@DM2PR06MB672.namprd06.prod.outlook.com>
Content-Type: text/plain; charset="utf-8"
Risk Management Solutions (RMS) is the world's leading provider of catastrophe risk models and information related to the financial impact of natural catastrophes. We have a team of 50 postdoctoral scientists and engineers based in London, and 70 in Newark (Calif.), building catastrophe models that predict the distributions of possible damage due to the effects of floods, tropical storms, extra-tropical storms, thunderstorms, and storm-surges. We use a combination of observed data, reanalysis data, numerical, statistical and engineering models and data assimilation. We are the pioneers in the development and application of complex statistical and numerical modelling methods for the quantification of natural hazard risk, and our risk models are the most detailed and comprehensive models of natural catastrophes produced anywhere in the world. Our clients include several hundred insurance and reinsurance companies as well as brokers, banks, hedge funds, regional and local governments, and multilateral agencies.
We're currently recruiting for a position in the Flood Modeling Team in London. The Flood team focuses on developing high-resolution, large-scale flood models which are used to assess flood risk. The modelling work carried out by the flood team encompasses all steps from hazard modelling to loss modelling. The department has an engaged working environment with a clear scientific, motivated and technological atmosphere.
Key Accountabilities & Deliverables:
* Further development of large scale rainfall-runoff models, stochastic rainfall processes, and defence failure models, and to seek for scientific and technological improvements in them;
* Advancement of hydraulic inundation methods;
* Calibration of hydrologic and hydraulic models;
* Benchmarking of model loss results against claims data and loss targets
* Perform rigorous QA and research into consistency between observed and modeled spatial patterns, seasonality of floods, flood magnitudes, and similar for loss patterns;
Experience Required:
* Candidates with a PhD in Hydrology or Computational Fluid Dynamics preferred, but a similar degree in Meteorology, Applied Mathematics, or Civil Engineering will also be considered;
* Must have a strong analytical mind-set;
* Strong programming skills (Fortran, R, bash, csh, python, awk and sed);
* Experience working with GIS-tools;
* Prior experience of working on large data sets in a Linux/Unix environment;
* Strong personal motivation, combined with an ability to work as part of a team, and to communicate results;
* Experience with model development, usage of GPUs for large compute jobs, data-assimilation and/or forecasting environments, SQL, and a strong publication record are considered an advantage.
* Experience working with Spark, C#, Java, is considered an advantage.
If you are interested, please send an email, with a covering letter and CV, to london.recruiting@rms.com. Appropriate candidates will be invited for interview in London.
Thanks,
Arno
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Message: 2
Date: Sat, 19 Dec 2015 05:44:47 +0000
From: Sue Grimmond <c.s.grimmond@reading.ac.uk>
To: "met-jobs@lists.reading.ac.uk" <met-jobs@lists.reading.ac.uk>
Subject: [Met-jobs] NERC PhD Case Studentship: Surface fluxes,
temperatures and boundary layer evolution at the building greyzone in
London
Message-ID:
<5736C312DA4AA64790B3520E686C821EA17C62ED@vime-mbx4.rdg.ac.uk>
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Case Studentship: Be involved in the next generation of urban climate modelling in operational numerical weather prediction and state of the art observations.
Surface fluxes, temperatures and boundary layer evolution at the building greyzone in London
Supervisors: Prof Sue Grimmond (University of Reading), Dr Sylvia Bohnenstengel (Met Office@ Reading), Dr Humphrey Lean (Met Office@ Reading), Dr Martin Best (Met Office, Exeter)
Funding: NERC Case Studentship (with the Met Office)
The next generation of weather and climate models will have higher spatial resolution. Versions now under development are at 500, 330, 100 and 50 m resolution compared to the current 1.5 km used routinely by the Met Office (the so-called UKV version of the Unified Model (UM)).This greater resolution will enable conditions across cities to be resolved with important implications for forecasts and decision-making, particularly under hazardous situations. The proposed research will assess these new modelling capabilities, specifically using a network of observations in London to identify deficiencies/strengths and to work to improve their performance.
In the context of cities, enhanced spatial resolution of the UKV means that the 3-dimensional nature of the urban environment has to be addressed in more detail. To do this the urban land surface model used within the UKV is being updated to include MORUSES (Met Office Reading Urban Surface Exchange Scheme, Porson et al. 2010, QJRMS) (via JULES - Joint UK Land Environment Simulator). MORUSES calculates the surface energy balance as a function of the spatially varying street canyon geometry. MORUSES uses grid scale building geometry to calculate effective roughness lengths for heat via a resistance network taking into account 3 different flow regimes in street canyons. This allows the variability of sensible heat over urban areas (well documented observationally) to be captured. MORUSES simulates fluxes of heat and momentum in the inertial sublayer at resolutions of O(1km). However, higher resolutions approach the 'building grey zone', where large buildings/streets start to become resolved. The building greyzone problem, and larger inhomogeneity at O(100m) scales, raise questions as to whether the 'effective roughness length' concept for heat and momentum can parametrise these exchanges, or if a vertically distributed approach to parametrise these exchanges is needed.
The research proposed here aims to test MORUSES (and higher resolution models) in London for a wide range of meteorological conditions using a wide range of point and spatially representative meteorological observations drawing on data from the London Urban Meteorology Observatory (LUMO)(www.met.reading.ac.uk/micromet<http://www.met.reading.ac.uk/micromet>). . The London observational network also provides a unique opportunity to undertake 3-d model evaluation at multiple, nested scales. Data to be used include turbulent sensible heat fluxes determined by eddy covariance (EC) and scintillometry techniques; boundary layer height and cloud cover using ceilometry; and surface temperatures from fast response infra-red cameras.
Specifically the student will
* develop O(100m) input dataset for MORUSES and compare against UKV
* develop scale-appropriate products for model evaluation
* compare performance of MORUSES at different resolutions against observations
* test the MORUSES approach for high-rise buildings
* test evolution of the boundary layer simulated by the model against lidar derived BL height
The studentship provides an excellent opportunity to gain skills in state of the art observations and their analysis; insights into urban land-surface schemes; and real-time assessment. This research will improve state of the art modelling in urban environments and make significant contributions to urban observational work, theory and modelling.
Eligibility: UK/EU students with excellent undergraduate/Master's degrees in a relevant discipline. Strong computer programming skills an asset. Must meet NERC/RCUK eligibility requirements
Application process: Apply to Department of Meteorology PhD programme, University of Reading indicating this project.
http://www.met.reading.ac.uk/pg-research/pgrapplications.html
Best wishes
Sue
======================
Prof Sue Grimmond
Department of Meteorology, University of Reading,
Earley Gate, PO Box 243, Reading, RG6 6BB, UK
E: C.S.Grimmond@reading.ac.uk<mailto:C.S.Grimmond@reading.ac.uk>
T:+44 118 378 6248
Office: 2L77
http://www.met.reading.ac.uk/micromet/
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