The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling
The benefits of dynamical atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are to date unknown. We investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition (IC), lateral boundary conditio...
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description | The benefits of dynamical atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are to date unknown. We investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition (IC), lateral boundary condition (LBC), and stochastic physics perturbations within a convective‐scale ensemble coupled system for an extratropical cyclone case study. Towards this aim, we developed the first 18‐member, 2.2 km grid spacing ensemble regional coupled system (Ensemble‐RCS) with domain covering the British Isles and surrounding seas. Ensemble‐RCS coupled and uncoupled simulations of cyclone Ciara (February 2020) were performed. Adding stochastic perturbations to the model physics parametrizations enhances the ensemble spread of the uncoupled atmosphere‐only ensemble driven by IC and LBC perturbations, while slightly reducing (by up to 0.5 m·s−1) the median of the ensemble 95th percentile 10‐m wind speeds from its value of about 24 m·s−1 at peak time. A substantial proportion of this impact is attributable to Charnock parameter perturbations alone. By coupling the atmosphere‐only ensemble, with stochastic physics, to the ocean, the ensemble median and spread is mainly unaffected. However, additional coupling to waves reduces the median wind speed by 1 m·s−1, which leads to reductions of up to 70% in strong wind strike probability, and halving of the spatial coverage of high values (>50%) of this probability. Finally, we demonstrate the usefulness of two metrics originally developed for precipitation verification – the neighbourhood‐based Fraction Skill Score (FSS) and the object‐based Structure, Amplitude, Location (SAL) – for examining the spread in convective‐scale ensemble forecasts. It is concluded that coupling has a consistent impact across the ensemble members. Remarkably, the impact of coupling to waves is found to be comparable in size to that of adding IC, LBC and stochastic physics perturbations to the uncoupled atmosphere‐only ensemble simulation, implying that the dynamical coupling to ocean and sea‐state are important aspects of model uncertainty.
The benefits of atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are as yet unknown. We develop a new dynamically coupled convection‐permitting ensemble system for the British Isles and surrounding seas to investigate the respective impacts of atm |
doi_str_mv | 10.1002/qj.4225 |
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The benefits of atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are as yet unknown. We develop a new dynamically coupled convection‐permitting ensemble system for the British Isles and surrounding seas to investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition, lateral boundary condition and stochastic physics perturbations. 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We investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition (IC), lateral boundary condition (LBC), and stochastic physics perturbations within a convective‐scale ensemble coupled system for an extratropical cyclone case study. Towards this aim, we developed the first 18‐member, 2.2 km grid spacing ensemble regional coupled system (Ensemble‐RCS) with domain covering the British Isles and surrounding seas. Ensemble‐RCS coupled and uncoupled simulations of cyclone Ciara (February 2020) were performed. Adding stochastic perturbations to the model physics parametrizations enhances the ensemble spread of the uncoupled atmosphere‐only ensemble driven by IC and LBC perturbations, while slightly reducing (by up to 0.5 m·s−1) the median of the ensemble 95th percentile 10‐m wind speeds from its value of about 24 m·s−1 at peak time. A substantial proportion of this impact is attributable to Charnock parameter perturbations alone. By coupling the atmosphere‐only ensemble, with stochastic physics, to the ocean, the ensemble median and spread is mainly unaffected. However, additional coupling to waves reduces the median wind speed by 1 m·s−1, which leads to reductions of up to 70% in strong wind strike probability, and halving of the spatial coverage of high values (>50%) of this probability. Finally, we demonstrate the usefulness of two metrics originally developed for precipitation verification – the neighbourhood‐based Fraction Skill Score (FSS) and the object‐based Structure, Amplitude, Location (SAL) – for examining the spread in convective‐scale ensemble forecasts. It is concluded that coupling has a consistent impact across the ensemble members. Remarkably, the impact of coupling to waves is found to be comparable in size to that of adding IC, LBC and stochastic physics perturbations to the uncoupled atmosphere‐only ensemble simulation, implying that the dynamical coupling to ocean and sea‐state are important aspects of model uncertainty.
The benefits of atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are as yet unknown. We develop a new dynamically coupled convection‐permitting ensemble system for the British Isles and surrounding seas to investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition, lateral boundary condition and stochastic physics perturbations. We find that the sensitivity of the ensemble to coupling to waves is comparable in size to that of ensemble perturbations and is consistent across the ensemble members.</description><subject>Atmosphere</subject><subject>atmosphere–ocean–wave coupling</subject><subject>Boundary conditions</subject><subject>convective‐scale ensemble forecasts</subject><subject>Cyclones</subject><subject>Ensemble forecasting</subject><subject>Extratropical cyclones</subject><subject>FSS</subject><subject>initial condition error</subject><subject>Oceans</subject><subject>Perturbations</subject><subject>Physics</subject><subject>Probability theory</subject><subject>SAL</subject><subject>stochastic physics perturbations</subject><subject>Strong winds</subject><subject>surface wind speeds</subject><subject>Weather forecasting</subject><subject>Wind</subject><subject>Wind speed</subject><issn>0035-9009</issn><issn>1477-870X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp1kM1KAzEUhYMoWKv4CgEXLmTqzfxlZinFXwoiVHAXMuGOTZlOpknaOit9BME39ElMrVtXZ3G-ey7nEHLKYMQA4svlfJTGcbZHBizlPCo4vOyTAUCSRSVAeUiOnJsDQMZjPiDv0xlSh63TXq-176mpaWdNJSvdaOe1osq0a1TBxe-PT6dkg7Q2FpV03m1p2VJ881Z6azodbKp61ZgWqTdU-oVx3QxtuP0yCmUbdCPXGFJXXaPb12NyUMvG4cmfDsnzzfV0fBdNHm_vx1eTSCWhTJRXDBFQ1pCoPFVJGqoCr4GnCjkkXMkqjRXLIOVQgGQlFKVknJUly2JZ1MmQnO1yQ7nlCp0Xc7OybXgp4jzJioJBDoE631HKGucs1qKzeiFtLxiI7bpiORfbdQN5sSM3usH-P0w8PfzSPyp4fxE</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Gentile, Emanuele S.</creator><creator>Gray, Suzanne L.</creator><creator>Lewis, Huw W.</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-8658-362X</orcidid><orcidid>https://orcid.org/0000-0003-3581-6459</orcidid><orcidid>https://orcid.org/0000-0002-6878-5145</orcidid></search><sort><creationdate>202201</creationdate><title>The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling</title><author>Gentile, Emanuele S. ; Gray, Suzanne L. ; Lewis, Huw W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3225-6b1ee0eaf03c64c3410007f074ce7037cab42c15047080a19089a17199152a8f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Atmosphere</topic><topic>atmosphere–ocean–wave coupling</topic><topic>Boundary conditions</topic><topic>convective‐scale ensemble forecasts</topic><topic>Cyclones</topic><topic>Ensemble forecasting</topic><topic>Extratropical cyclones</topic><topic>FSS</topic><topic>initial condition error</topic><topic>Oceans</topic><topic>Perturbations</topic><topic>Physics</topic><topic>Probability theory</topic><topic>SAL</topic><topic>stochastic physics perturbations</topic><topic>Strong winds</topic><topic>surface wind speeds</topic><topic>Weather forecasting</topic><topic>Wind</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gentile, Emanuele S.</creatorcontrib><creatorcontrib>Gray, Suzanne L.</creatorcontrib><creatorcontrib>Lewis, Huw W.</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Quarterly journal of the Royal Meteorological Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gentile, Emanuele S.</au><au>Gray, Suzanne L.</au><au>Lewis, Huw W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling</atitle><jtitle>Quarterly journal of the Royal Meteorological Society</jtitle><date>2022-01</date><risdate>2022</risdate><volume>148</volume><issue>743</issue><spage>685</spage><epage>710</epage><pages>685-710</pages><issn>0035-9009</issn><eissn>1477-870X</eissn><abstract>The benefits of dynamical atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are to date unknown. We investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition (IC), lateral boundary condition (LBC), and stochastic physics perturbations within a convective‐scale ensemble coupled system for an extratropical cyclone case study. Towards this aim, we developed the first 18‐member, 2.2 km grid spacing ensemble regional coupled system (Ensemble‐RCS) with domain covering the British Isles and surrounding seas. Ensemble‐RCS coupled and uncoupled simulations of cyclone Ciara (February 2020) were performed. Adding stochastic perturbations to the model physics parametrizations enhances the ensemble spread of the uncoupled atmosphere‐only ensemble driven by IC and LBC perturbations, while slightly reducing (by up to 0.5 m·s−1) the median of the ensemble 95th percentile 10‐m wind speeds from its value of about 24 m·s−1 at peak time. A substantial proportion of this impact is attributable to Charnock parameter perturbations alone. By coupling the atmosphere‐only ensemble, with stochastic physics, to the ocean, the ensemble median and spread is mainly unaffected. However, additional coupling to waves reduces the median wind speed by 1 m·s−1, which leads to reductions of up to 70% in strong wind strike probability, and halving of the spatial coverage of high values (>50%) of this probability. Finally, we demonstrate the usefulness of two metrics originally developed for precipitation verification – the neighbourhood‐based Fraction Skill Score (FSS) and the object‐based Structure, Amplitude, Location (SAL) – for examining the spread in convective‐scale ensemble forecasts. It is concluded that coupling has a consistent impact across the ensemble members. Remarkably, the impact of coupling to waves is found to be comparable in size to that of adding IC, LBC and stochastic physics perturbations to the uncoupled atmosphere‐only ensemble simulation, implying that the dynamical coupling to ocean and sea‐state are important aspects of model uncertainty.
The benefits of atmosphere–ocean–wave coupling in probabilistic weather forecasts generated using convective‐scale ensemble prediction systems are as yet unknown. We develop a new dynamically coupled convection‐permitting ensemble system for the British Isles and surrounding seas to investigate the respective impacts of atmosphere–ocean–wave coupling, and initial condition, lateral boundary condition and stochastic physics perturbations. We find that the sensitivity of the ensemble to coupling to waves is comparable in size to that of ensemble perturbations and is consistent across the ensemble members.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/qj.4225</doi><tpages>26</tpages><orcidid>https://orcid.org/0000-0001-8658-362X</orcidid><orcidid>https://orcid.org/0000-0003-3581-6459</orcidid><orcidid>https://orcid.org/0000-0002-6878-5145</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Atmosphere atmosphere–ocean–wave coupling Boundary conditions convective‐scale ensemble forecasts Cyclones Ensemble forecasting Extratropical cyclones FSS initial condition error Oceans Perturbations Physics Probability theory SAL stochastic physics perturbations Strong winds surface wind speeds Weather forecasting Wind Wind speed |
title | The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling |
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