Met Office & Hong Kong Observatory Project Presentation Day, 10 November 2021

In Summer 2021, MPE CDT Echo Students took part in nine-week research internships with either the Met Office or the Hong Kong Observatory. These were carried out remotely, although some were able to meet their Met Office supervisor in person.

On 10 November 2021 they presented the results of their research at a meeting held in The Meadow Suite in Park House at The University of Reading to an audience that included Brian Golding and Ken Mylne from the Met Office; Dan Crisan and Colin Cotter from Imperial College London; and Jennifer Scott, Ted Shepherd, Valerio Lucarini and Janet Fillingham from the University of Reading.

MOTR/HKO Presentation Day 10 November 2021

Met Office Projects:

Calvin Nesbitt “Future changes in temperature extremes over UK cities” 

Lois Baker “Validation of large oscillations in equatorially trapped meridional overturning circulations using the TAO mooring array” 

James Woodfield “Limiting advection algorithms, and dimensionally split schemes” 

Oliver Street “Investigating the numerical implementation of moisture within the shallow water miniapp” 

Ryosuke Kurashina “Impacts of volcanic ash on the UK” 

Thomas Gregory “Regional clustering in forecast temperature calibration” 

Lily Greig “A comparison of simplified and full complexity ERSEM models of the North West European Shelf” 

Cathie Wells “Impact of climate change on flight duration and efficiency” 

Oliver Phillips “A deep learning approach to better simulate ice crystal bulk optical properties” 

Philipp Breul “Urban Tree Species Identification Using Satellite Data” 

Sam Harrison “Ash Flow from Icelandic Volcanoes” 

Swinda Falkena “Analysis of United Kingdom daily temperature extremes in summer using generalised additive models” 

Hong Kong Observatory Projects:

Chiara Maiocchi “Improve significant convection forecast by blending satellite nowcast with numerical model outputs” 

Niccolo Zagli “Predicting extreme events by using Numerical Weather Predictions and observational data in the Hong Kong Area”