Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble
A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km...
Gespeichert in:
Veröffentlicht in: | Journal of climate 2020-04, Vol.33 (7), p.2557-2583 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2583 |
---|---|
container_issue | 7 |
container_start_page | 2557 |
container_title | Journal of climate |
container_volume | 33 |
creator | Roberts, Malcolm John Camp, Joanne Seddon, Jon Vidale, Pier Luigi Hodges, Kevin Vanniere, Benoit Mecking, Jenny Haarsma, Rein Bellucci, Alessio Scoccimarro, Enrico Caron, Louis-Philippe Chauvin, Fabrice Terray, Laurent Valcke, Sophie Moine, Marie-Pierre Putrasahan, Dian Roberts, Christopher Senan, Retish Zarzycki, Colin Ullrich, Paul |
description | A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ∼0.5 to ∼0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise. |
doi_str_mv | 10.1175/jcli-d-19-0639.1 |
format | Article |
fullrecord | <record><control><sourceid>jstor_osti_</sourceid><recordid>TN_cdi_osti_scitechconnect_1803074</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>26916877</jstor_id><sourcerecordid>26916877</sourcerecordid><originalsourceid>FETCH-LOGICAL-c509t-5e4bfafc971f54d17eec3b16d4498edb2198a1d20c71786cdb9eb1f2c1a6d3b53</originalsourceid><addsrcrecordid>eNo9kcFq3DAQhk1podu0914Koj314FQjS5Z0XLbbrssuDdukVyHLclaLbG0suZBb3yFvmCepNy5hBgZmvv-H4c-y94AvATj7cjTe5U0OMsdlIS_hRbYARnCOKSUvswUWkuaCM_Y6exPjEWMgJcaLrK-6kzYJhRbtQmM92tsY_Jhc6NHU10M4OaM9Wt0bH3qLfrlu9PrpfBNdf4vSwaKNuz1Mul119fj34Wpf7Za_1_sl2o0-ue7Jdd1H29Xevs1etdpH--7_vMhuvq2vV5t8-_N7tVpuc8OwTDmztG51aySHltEGuLWmqKFsKJXCNjUBKTQ0BBsOXJSmqaWtoSUGdNkUNSsuso-zb4jJqWhcsuZgQt9bkxQIXGBOJ-jzDB20V6fBdXq4V0E7tVlu1XmHKS-mkn9gYj_N7GkId6ONSR3DOPTTD4oUkpSUCcEnCs-UGUKMg22fbQGrc0zqx2pbqa8KpDrHpM7GH2bJMaYwPPOklFAKzot_1tiP-A</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2392645887</pqid></control><display><type>article</type><title>Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble</title><source>American Meteorological Society</source><source>JSTOR Archive Collection A-Z Listing</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Roberts, Malcolm John ; Camp, Joanne ; Seddon, Jon ; Vidale, Pier Luigi ; Hodges, Kevin ; Vanniere, Benoit ; Mecking, Jenny ; Haarsma, Rein ; Bellucci, Alessio ; Scoccimarro, Enrico ; Caron, Louis-Philippe ; Chauvin, Fabrice ; Terray, Laurent ; Valcke, Sophie ; Moine, Marie-Pierre ; Putrasahan, Dian ; Roberts, Christopher ; Senan, Retish ; Zarzycki, Colin ; Ullrich, Paul</creator><creatorcontrib>Roberts, Malcolm John ; Camp, Joanne ; Seddon, Jon ; Vidale, Pier Luigi ; Hodges, Kevin ; Vanniere, Benoit ; Mecking, Jenny ; Haarsma, Rein ; Bellucci, Alessio ; Scoccimarro, Enrico ; Caron, Louis-Philippe ; Chauvin, Fabrice ; Terray, Laurent ; Valcke, Sophie ; Moine, Marie-Pierre ; Putrasahan, Dian ; Roberts, Christopher ; Senan, Retish ; Zarzycki, Colin ; Ullrich, Paul ; Univ. of California, Davis, CA (United States)</creatorcontrib><description>A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ∼0.5 to ∼0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.</description><identifier>ISSN: 0894-8755</identifier><identifier>EISSN: 1520-0442</identifier><identifier>DOI: 10.1175/jcli-d-19-0639.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Algorithms ; Atmosphere ; Climate ; Climate models ; Climate variability ; Climatology ; Computer simulation ; Cyclones ; Datasets ; Design ; Earth Sciences ; Energy ; ENVIRONMENTAL SCIENCES ; Extreme events ; Hurricanes ; Interannual variability ; Meteorology & Atmospheric Sciences ; Model evaluation/performance ; Oceans ; Optical properties ; Resolution ; Sciences of the Universe ; Simulation ; Spatial distribution ; SPECIAL U.S. CLIVAR Hurricanes COLLECTION ; Storm structure ; Storms ; Tracking ; Tropical climate ; Tropical climates ; Tropical cyclones ; Variability ; Weather</subject><ispartof>Journal of climate, 2020-04, Vol.33 (7), p.2557-2583</ispartof><rights>2020 American Meteorological Society</rights><rights>Copyright American Meteorological Society Apr 2020</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c509t-5e4bfafc971f54d17eec3b16d4498edb2198a1d20c71786cdb9eb1f2c1a6d3b53</citedby><cites>FETCH-LOGICAL-c509t-5e4bfafc971f54d17eec3b16d4498edb2198a1d20c71786cdb9eb1f2c1a6d3b53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26916877$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26916877$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,780,784,803,885,3681,27924,27925,58017,58250</link.rule.ids><backlink>$$Uhttps://cnrs.hal.science/hal-04737379$$DView record in HAL$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/servlets/purl/1803074$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Roberts, Malcolm John</creatorcontrib><creatorcontrib>Camp, Joanne</creatorcontrib><creatorcontrib>Seddon, Jon</creatorcontrib><creatorcontrib>Vidale, Pier Luigi</creatorcontrib><creatorcontrib>Hodges, Kevin</creatorcontrib><creatorcontrib>Vanniere, Benoit</creatorcontrib><creatorcontrib>Mecking, Jenny</creatorcontrib><creatorcontrib>Haarsma, Rein</creatorcontrib><creatorcontrib>Bellucci, Alessio</creatorcontrib><creatorcontrib>Scoccimarro, Enrico</creatorcontrib><creatorcontrib>Caron, Louis-Philippe</creatorcontrib><creatorcontrib>Chauvin, Fabrice</creatorcontrib><creatorcontrib>Terray, Laurent</creatorcontrib><creatorcontrib>Valcke, Sophie</creatorcontrib><creatorcontrib>Moine, Marie-Pierre</creatorcontrib><creatorcontrib>Putrasahan, Dian</creatorcontrib><creatorcontrib>Roberts, Christopher</creatorcontrib><creatorcontrib>Senan, Retish</creatorcontrib><creatorcontrib>Zarzycki, Colin</creatorcontrib><creatorcontrib>Ullrich, Paul</creatorcontrib><creatorcontrib>Univ. of California, Davis, CA (United States)</creatorcontrib><title>Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble</title><title>Journal of climate</title><description>A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ∼0.5 to ∼0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.</description><subject>Algorithms</subject><subject>Atmosphere</subject><subject>Climate</subject><subject>Climate models</subject><subject>Climate variability</subject><subject>Climatology</subject><subject>Computer simulation</subject><subject>Cyclones</subject><subject>Datasets</subject><subject>Design</subject><subject>Earth Sciences</subject><subject>Energy</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>Extreme events</subject><subject>Hurricanes</subject><subject>Interannual variability</subject><subject>Meteorology & Atmospheric Sciences</subject><subject>Model evaluation/performance</subject><subject>Oceans</subject><subject>Optical properties</subject><subject>Resolution</subject><subject>Sciences of the Universe</subject><subject>Simulation</subject><subject>Spatial distribution</subject><subject>SPECIAL U.S. CLIVAR Hurricanes COLLECTION</subject><subject>Storm structure</subject><subject>Storms</subject><subject>Tracking</subject><subject>Tropical climate</subject><subject>Tropical climates</subject><subject>Tropical cyclones</subject><subject>Variability</subject><subject>Weather</subject><issn>0894-8755</issn><issn>1520-0442</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNo9kcFq3DAQhk1podu0914Koj314FQjS5Z0XLbbrssuDdukVyHLclaLbG0suZBb3yFvmCepNy5hBgZmvv-H4c-y94AvATj7cjTe5U0OMsdlIS_hRbYARnCOKSUvswUWkuaCM_Y6exPjEWMgJcaLrK-6kzYJhRbtQmM92tsY_Jhc6NHU10M4OaM9Wt0bH3qLfrlu9PrpfBNdf4vSwaKNuz1Mul119fj34Wpf7Za_1_sl2o0-ue7Jdd1H29Xevs1etdpH--7_vMhuvq2vV5t8-_N7tVpuc8OwTDmztG51aySHltEGuLWmqKFsKJXCNjUBKTQ0BBsOXJSmqaWtoSUGdNkUNSsuso-zb4jJqWhcsuZgQt9bkxQIXGBOJ-jzDB20V6fBdXq4V0E7tVlu1XmHKS-mkn9gYj_N7GkId6ONSR3DOPTTD4oUkpSUCcEnCs-UGUKMg22fbQGrc0zqx2pbqa8KpDrHpM7GH2bJMaYwPPOklFAKzot_1tiP-A</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Roberts, Malcolm John</creator><creator>Camp, Joanne</creator><creator>Seddon, Jon</creator><creator>Vidale, Pier Luigi</creator><creator>Hodges, Kevin</creator><creator>Vanniere, Benoit</creator><creator>Mecking, Jenny</creator><creator>Haarsma, Rein</creator><creator>Bellucci, Alessio</creator><creator>Scoccimarro, Enrico</creator><creator>Caron, Louis-Philippe</creator><creator>Chauvin, Fabrice</creator><creator>Terray, Laurent</creator><creator>Valcke, Sophie</creator><creator>Moine, Marie-Pierre</creator><creator>Putrasahan, Dian</creator><creator>Roberts, Christopher</creator><creator>Senan, Retish</creator><creator>Zarzycki, Colin</creator><creator>Ullrich, Paul</creator><general>American Meteorological Society</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>7X2</scope><scope>7XB</scope><scope>88F</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M0K</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope><scope>1XC</scope><scope>VOOES</scope><scope>OIOZB</scope><scope>OTOTI</scope></search><sort><creationdate>20200401</creationdate><title>Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble</title><author>Roberts, Malcolm John ; Camp, Joanne ; Seddon, Jon ; Vidale, Pier Luigi ; Hodges, Kevin ; Vanniere, Benoit ; Mecking, Jenny ; Haarsma, Rein ; Bellucci, Alessio ; Scoccimarro, Enrico ; Caron, Louis-Philippe ; Chauvin, Fabrice ; Terray, Laurent ; Valcke, Sophie ; Moine, Marie-Pierre ; Putrasahan, Dian ; Roberts, Christopher ; Senan, Retish ; Zarzycki, Colin ; Ullrich, Paul</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c509t-5e4bfafc971f54d17eec3b16d4498edb2198a1d20c71786cdb9eb1f2c1a6d3b53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Atmosphere</topic><topic>Climate</topic><topic>Climate models</topic><topic>Climate variability</topic><topic>Climatology</topic><topic>Computer simulation</topic><topic>Cyclones</topic><topic>Datasets</topic><topic>Design</topic><topic>Earth Sciences</topic><topic>Energy</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>Extreme events</topic><topic>Hurricanes</topic><topic>Interannual variability</topic><topic>Meteorology & Atmospheric Sciences</topic><topic>Model evaluation/performance</topic><topic>Oceans</topic><topic>Optical properties</topic><topic>Resolution</topic><topic>Sciences of the Universe</topic><topic>Simulation</topic><topic>Spatial distribution</topic><topic>SPECIAL U.S. CLIVAR Hurricanes COLLECTION</topic><topic>Storm structure</topic><topic>Storms</topic><topic>Tracking</topic><topic>Tropical climate</topic><topic>Tropical climates</topic><topic>Tropical cyclones</topic><topic>Variability</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Roberts, Malcolm John</creatorcontrib><creatorcontrib>Camp, Joanne</creatorcontrib><creatorcontrib>Seddon, Jon</creatorcontrib><creatorcontrib>Vidale, Pier Luigi</creatorcontrib><creatorcontrib>Hodges, Kevin</creatorcontrib><creatorcontrib>Vanniere, Benoit</creatorcontrib><creatorcontrib>Mecking, Jenny</creatorcontrib><creatorcontrib>Haarsma, Rein</creatorcontrib><creatorcontrib>Bellucci, Alessio</creatorcontrib><creatorcontrib>Scoccimarro, Enrico</creatorcontrib><creatorcontrib>Caron, Louis-Philippe</creatorcontrib><creatorcontrib>Chauvin, Fabrice</creatorcontrib><creatorcontrib>Terray, Laurent</creatorcontrib><creatorcontrib>Valcke, Sophie</creatorcontrib><creatorcontrib>Moine, Marie-Pierre</creatorcontrib><creatorcontrib>Putrasahan, Dian</creatorcontrib><creatorcontrib>Roberts, Christopher</creatorcontrib><creatorcontrib>Senan, Retish</creatorcontrib><creatorcontrib>Zarzycki, Colin</creatorcontrib><creatorcontrib>Ullrich, Paul</creatorcontrib><creatorcontrib>Univ. of California, Davis, CA (United States)</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Agricultural Science Database</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Journal of climate</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Roberts, Malcolm John</au><au>Camp, Joanne</au><au>Seddon, Jon</au><au>Vidale, Pier Luigi</au><au>Hodges, Kevin</au><au>Vanniere, Benoit</au><au>Mecking, Jenny</au><au>Haarsma, Rein</au><au>Bellucci, Alessio</au><au>Scoccimarro, Enrico</au><au>Caron, Louis-Philippe</au><au>Chauvin, Fabrice</au><au>Terray, Laurent</au><au>Valcke, Sophie</au><au>Moine, Marie-Pierre</au><au>Putrasahan, Dian</au><au>Roberts, Christopher</au><au>Senan, Retish</au><au>Zarzycki, Colin</au><au>Ullrich, Paul</au><aucorp>Univ. of California, Davis, CA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble</atitle><jtitle>Journal of climate</jtitle><date>2020-04-01</date><risdate>2020</risdate><volume>33</volume><issue>7</issue><spage>2557</spage><epage>2583</epage><pages>2557-2583</pages><issn>0894-8755</issn><eissn>1520-0442</eissn><abstract>A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ∼0.5 to ∼0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/jcli-d-19-0639.1</doi><tpages>27</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0894-8755 |
ispartof | Journal of climate, 2020-04, Vol.33 (7), p.2557-2583 |
issn | 0894-8755 1520-0442 |
language | eng |
recordid | cdi_osti_scitechconnect_1803074 |
source | American Meteorological Society; JSTOR Archive Collection A-Z Listing; EZB-FREE-00999 freely available EZB journals |
subjects | Algorithms Atmosphere Climate Climate models Climate variability Climatology Computer simulation Cyclones Datasets Design Earth Sciences Energy ENVIRONMENTAL SCIENCES Extreme events Hurricanes Interannual variability Meteorology & Atmospheric Sciences Model evaluation/performance Oceans Optical properties Resolution Sciences of the Universe Simulation Spatial distribution SPECIAL U.S. CLIVAR Hurricanes COLLECTION Storm structure Storms Tracking Tropical climate Tropical climates Tropical cyclones Variability Weather |
title | Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T05%3A58%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_osti_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Impact%20of%20Model%20Resolution%20on%20Tropical%20Cyclone%20Simulation%20Using%20the%20HighResMIP%E2%80%93PRIMAVERA%20Multimodel%20Ensemble&rft.jtitle=Journal%20of%20climate&rft.au=Roberts,%20Malcolm%20John&rft.aucorp=Univ.%20of%20California,%20Davis,%20CA%20(United%20States)&rft.date=2020-04-01&rft.volume=33&rft.issue=7&rft.spage=2557&rft.epage=2583&rft.pages=2557-2583&rft.issn=0894-8755&rft.eissn=1520-0442&rft_id=info:doi/10.1175/jcli-d-19-0639.1&rft_dat=%3Cjstor_osti_%3E26916877%3C/jstor_osti_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2392645887&rft_id=info:pmid/&rft_jstor_id=26916877&rfr_iscdi=true |