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Laura C. Dawkins

Researcher at Met Office

Publications -  17
Citations -  202

Laura C. Dawkins is an academic researcher from Met Office. The author has contributed to research in topics: Environmental science & Computer science. The author has an hindex of 4, co-authored 11 publications receiving 121 citations. Previous affiliations of Laura C. Dawkins include University of Exeter.

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The XWS open access catalogue of extreme European windstorms from 1979 to 2012

TL;DR: The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe in the period 1979-2012 as discussed by the authors.
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The 21st century decline in damaging European windstorms

TL;DR: In this article, the authors explored how and why windstorm characteristics have changed in recent years, based on 6103 high-resolution model-generated historical footprints (1979-2014), representing the whole European domain.
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The Advanced Meteorology Explorer: a novel stochastic, gridded daily rainfall generator

TL;DR: In this paper , the Advanced Meteorology Explorer (AME) framework is proposed for the simulation of physically consistent synthetic daily rainfall data, coherently in space and time on a high-resolution grid over a region of interest.
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Influencing transport behaviour: a Bayesian modelling approach for segmentation of social surveys

TL;DR: This work identifies that individuals that predominantly commute by public transport, but also sometimes motor vehicle, do so on average up to one day per week less often, if they are strongly concerned about the environment, demonstrating how an intervention to promote environmental awareness could greatly reduce motor vehicle usage within this group.
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Where Is the Clean Air? A Bayesian Decision Framework for Personalised Cyclist Route Selection Using R-INLA

TL;DR: A novel hierarchical spatio-temporal model for city air quality that includes buildings as barriers and captures covariate information is presented, providing the user with Bayes-optimal journey decision support.