{"id":{"repo_id":"east-anglia","oai_identifier":"oai:ueaeprints.uea.ac.uk:47925"},"canonical_url":"https://search.dev.ndltd.org/etd/east-anglia/oai:ueaeprints.uea.ac.uk:47925","repository":{"repo_id":"east-anglia","name":"University of East Anglia","base_url":"https://ueaeprints.uea.ac.uk/cgi/oai2"},"display":{"title":"The UK wind regime - Observational trends and extreme event analysis and modelling","abstract":"Abstract The UK has one of the most variable wind climates; NW Europe as a whole is a challenging region for forecast- and climate-modelling alike. In Europe, strong winds within extra-tropical cyclones (ETCs) remain on average the most economically significant weather peril when averaged over multiple years, so an understanding how ETCs cause extreme surface winds and how these extremes vary over time is crucial. An assessment of the 1980-2010 UK wind regime is presented based on a unique 40-station network of 10m hourly mean windspeed and daily maximum gustspeed (DMGS) surface station measurements. The regime is assessed, in the context of longer- and larger-scale wind variability, in terms of temporal trends, seasonality, spatial variation, distribution and extremes. Annual mean windspeed ranged from 4.4 to 5.4 ms-1 (a 22% difference) with 2010 recording the lowest annual network mean windspeed over the period, attracting the attention of the insurance and wind energy sectors, both highly exposed to windspeed variations. A short subjective climatology (2008-2010) is developed of the ETCs and their sub-storm features which are associated with the strongest DMGSs. The little studied UK Quasi-linear convective systems (QLCSs) and pseudo-QLCSs are found to account for 22% of the top 1% of DMGSs, with the better known Sting Jet accounting for at most 5%. This same climatology of 2008-10 ETCs then forms the basis of performance assessments of global forecast ensemble systems. At T+48, an ensemble consisting of just the ECMWF and Canadian EPS members (total-70) is found to capture the same set of extreme events as an ensemble consisting of nine global centres (157-239) highlighting the value of using model physics perturbations at this range. A prominent ETC, Emma, then forms the basis of a high-resolution model sensitivity analysis using the Weather Research and Forecasting model. Surface wind simulations display greater sensitivity to different cloud microphysics schemes and to horizontal resolution than to vertical resolution, the former highlighting the importance of diabatic processes within extreme European ETCs.","abstract_html":"Abstract The UK has one of the most variable wind climates; NW Europe as a whole is a challenging region for forecast- and climate-modelling alike. In Europe, strong winds within extra-tropical cyclones (ETCs) remain on average the most economically significant weather peril when averaged over multiple years, so an understanding how ETCs cause extreme surface winds and how these extremes vary over time is crucial. An assessment of the 1980-2010 UK wind regime is presented based on a unique 40-station network of 10m hourly mean windspeed and daily maximum gustspeed (DMGS) surface station measurements. The regime is assessed, in the context of longer- and larger-scale wind variability, in terms of temporal trends, seasonality, spatial variation, distribution and extremes. Annual mean windspeed ranged from 4.4 to 5.4 ms-1 (a 22% difference) with 2010 recording the lowest annual network mean windspeed over the period, attracting the attention of the insurance and wind energy sectors, both highly exposed to windspeed variations. A short subjective climatology (2008-2010) is developed of the ETCs and their sub-storm features which are associated with the strongest DMGSs. The little studied UK Quasi-linear convective systems (QLCSs) and pseudo-QLCSs are found to account for 22% of the top 1% of DMGSs, with the better known Sting Jet accounting for at most 5%. This same climatology of 2008-10 ETCs then forms the basis of performance assessments of global forecast ensemble systems. At T+48, an ensemble consisting of just the ECMWF and Canadian EPS members (total-70) is found to capture the same set of extreme events as an ensemble consisting of nine global centres (157-239) highlighting the value of using model physics perturbations at this range. A prominent ETC, Emma, then forms the basis of a high-resolution model sensitivity analysis using the Weather Research and Forecasting model. Surface wind simulations display greater sensitivity to different cloud microphysics schemes and to horizontal resolution than to vertical resolution, the former highlighting the importance of diabatic processes within extreme European ETCs.","abstract_has_math":false,"creators":["Earl, Nick"],"institution":"University of East Anglia","degree_name":"phd","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-06","date_published":"2013-06","updated_at":"2026-07-24T02:11:56Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Earl, Nick"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013-06"]},{"key":"dc:date.issued","label":"Date","values":["2013-06"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Environmental Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of East Anglia"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://ueaeprints.uea.ac.uk/id/eprint/47925/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["phd"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://ueaeprints.uea.ac.uk/id/eprint/47925/1/2013EarlNEPhD.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Abstract The UK has one of the most variable wind climates; NW Europe as a whole is a challenging region for forecast- and climate-modelling alike. In Europe, strong winds within extra-tropical cyclones (ETCs) remain on average the most economically significant weather peril when averaged over multiple years, so an understanding how ETCs cause extreme surface winds and how these extremes vary over time is crucial. An assessment of the 1980-2010 UK wind regime is presented based on a unique 40-station network of 10m hourly mean windspeed and daily maximum gustspeed (DMGS) surface station measurements. The regime is assessed, in the context of longer- and larger-scale wind variability, in terms of temporal trends, seasonality, spatial variation, distribution and extremes. Annual mean windspeed ranged from 4.4 to 5.4 ms-1 (a 22% difference) with 2010 recording the lowest annual network mean windspeed over the period, attracting the attention of the insurance and wind energy sectors, both highly exposed to windspeed variations. A short subjective climatology (2008-2010) is developed of the ETCs and their sub-storm features which are associated with the strongest DMGSs. The little studied UK Quasi-linear convective systems (QLCSs) and pseudo-QLCSs are found to account for 22% of the top 1% of DMGSs, with the better known Sting Jet accounting for at most 5%. This same climatology of 2008-10 ETCs then forms the basis of performance assessments of global forecast ensemble systems. At T+48, an ensemble consisting of just the ECMWF and Canadian EPS members (total-70) is found to capture the same set of extreme events as an ensemble consisting of nine global centres (157-239) highlighting the value of using model physics perturbations at this range. A prominent ETC, Emma, then forms the basis of a high-resolution model sensitivity analysis using the Weather Research and Forecasting model. Surface wind simulations display greater sensitivity to different cloud microphysics schemes and to horizontal resolution than to vertical resolution, the former highlighting the importance of diabatic processes within extreme European ETCs."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The UK wind regime - Observational trends and extreme event analysis and modelling"]}]}],"canonical_facts":{"dc:creator":["Earl, Nick"],"dc:date":["2013-06"],"dc:date.issued":["2013-06"],"dc:description.abstract":["Abstract The UK has one of the most variable wind climates; NW Europe as a whole is a challenging region for forecast- and climate-modelling alike. In Europe, strong winds within extra-tropical cyclones (ETCs) remain on average the most economically significant weather peril when averaged over multiple years, so an understanding how ETCs cause extreme surface winds and how these extremes vary over time is crucial. An assessment of the 1980-2010 UK wind regime is presented based on a unique 40-station network of 10m hourly mean windspeed and daily maximum gustspeed (DMGS) surface station measurements. The regime is assessed, in the context of longer- and larger-scale wind variability, in terms of temporal trends, seasonality, spatial variation, distribution and extremes. Annual mean windspeed ranged from 4.4 to 5.4 ms-1 (a 22% difference) with 2010 recording the lowest annual network mean windspeed over the period, attracting the attention of the insurance and wind energy sectors, both highly exposed to windspeed variations. A short subjective climatology (2008-2010) is developed of the ETCs and their sub-storm features which are associated with the strongest DMGSs. The little studied UK Quasi-linear convective systems (QLCSs) and pseudo-QLCSs are found to account for 22% of the top 1% of DMGSs, with the better known Sting Jet accounting for at most 5%. This same climatology of 2008-10 ETCs then forms the basis of performance assessments of global forecast ensemble systems. At T+48, an ensemble consisting of just the ECMWF and Canadian EPS members (total-70) is found to capture the same set of extreme events as an ensemble consisting of nine global centres (157-239) highlighting the value of using model physics perturbations at this range. A prominent ETC, Emma, then forms the basis of a high-resolution model sensitivity analysis using the Weather Research and Forecasting model. Surface wind simulations display greater sensitivity to different cloud microphysics schemes and to horizontal resolution than to vertical resolution, the former highlighting the importance of diabatic processes within extreme European ETCs."],"dc:format":["application/pdf"],"dc:identifier.uri":["https://ueaeprints.uea.ac.uk/id/eprint/47925/1/2013EarlNEPhD.pdf"],"dc:language":["en"],"dc:publisher.department":["School of Environmental Sciences"],"dc:publisher.institution":["University of East Anglia"],"dc:relation.isreferencedby":["https://ueaeprints.uea.ac.uk/id/eprint/47925/"],"dc:title":["The UK wind regime - Observational trends and extreme event analysis and modelling"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["phd"]},"updated_at":"2026-07-24T02:11:56Z"}