Realistic ocean initial condition for stimulating the successful prediction of extreme cold events in the 2020/2021 winter
In the first half of winter 2020/2021, several unprecedented cold events occurred in most parts of China and caused record-breaking low temperatures in many cities. However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first...
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description | In the first half of winter 2020/2021, several unprecedented cold events occurred in most parts of China and caused record-breaking low temperatures in many cities. However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first evaluated the short-term climate prediction skills in winter of the CAS-ESM-c global coupled model and revealed the key dynamic processes of the onset and development of 2020/2021 extreme cold events based on the ensemble forecasts starting on October 1st, 2020. Under the background provided by the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña), the model captured the abnormal meridional atmospheric pattern well, including the intensification of the Ural Blocking High and the negative phase of the Arctic Oscillation, forecasted the negative geopotential height anomalies over the Eastern Asian region, and finally, successfully predicted the outbreak of cold waves in December 2020 two months in advance. Moreover, the dominant differences in the initial ocean fields between the best and the worst forecast members were further compared to isolate the triggering factor for predicting cold events by CAS-ESM-c. The initial warm sea surface temperature over the Barents Sea can gradually form a meridional pattern between the warm Arctic and the cold Asian continent, which could lead to a reduction in the large-scale meridional temperature gradient at mid-high latitudes and weaken the atmospheric baroclinicity with more conducive to the southward outbreak of cold waves, highlighting that realistic Arctic ocean conditions in autumn can be reasonably assimilated into coupled models to stimulate the successful prediction of extreme cold events in the 2020/2021 winter. |
doi_str_mv | 10.1007/s00382-022-06557-x |
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However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first evaluated the short-term climate prediction skills in winter of the CAS-ESM-c global coupled model and revealed the key dynamic processes of the onset and development of 2020/2021 extreme cold events based on the ensemble forecasts starting on October 1st, 2020. Under the background provided by the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña), the model captured the abnormal meridional atmospheric pattern well, including the intensification of the Ural Blocking High and the negative phase of the Arctic Oscillation, forecasted the negative geopotential height anomalies over the Eastern Asian region, and finally, successfully predicted the outbreak of cold waves in December 2020 two months in advance. Moreover, the dominant differences in the initial ocean fields between the best and the worst forecast members were further compared to isolate the triggering factor for predicting cold events by CAS-ESM-c. The initial warm sea surface temperature over the Barents Sea can gradually form a meridional pattern between the warm Arctic and the cold Asian continent, which could lead to a reduction in the large-scale meridional temperature gradient at mid-high latitudes and weaken the atmospheric baroclinicity with more conducive to the southward outbreak of cold waves, highlighting that realistic Arctic ocean conditions in autumn can be reasonably assimilated into coupled models to stimulate the successful prediction of extreme cold events in the 2020/2021 winter.</description><identifier>ISSN: 0930-7575</identifier><identifier>EISSN: 1432-0894</identifier><identifier>DOI: 10.1007/s00382-022-06557-x</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Analysis ; Anomalies ; Arctic Ocean ; Arctic Oscillation ; Arctic region ; Atmospheric models ; autumn ; Barents Sea ; Baroclinic mode ; Baroclinity ; Blocking anticyclones ; China ; Climate models ; Climate prediction ; Climatology ; Cold ; Cold waves ; Cold weather ; Dynamic height ; Earth and Environmental Science ; Earth Sciences ; El Nino phenomena ; Ensemble forecasting ; Environmental aspects ; evolution ; Extreme cold ; Extreme low temperatures ; Extreme weather ; Geophysics/Geodesy ; Geopotential ; Geopotential height ; Height anomalies ; La Nina ; Low temperature ; Mathematical models ; Oceanography ; Oceans ; Outbreaks ; prediction ; Sea surface ; Sea surface temperature ; Surface temperature ; surface water temperature ; synergism ; Synergistic effect ; Temperature gradients ; Ural blocking ; Weather forecasting ; Winter</subject><ispartof>Climate dynamics, 2023-07, Vol.61 (1-2), p.33-46</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>COPYRIGHT 2023 Springer</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c500t-16b504ad5c0a03bdee1e380b8af918928959fbe8a6151d6b83ee4bcb69d52e8c3</citedby><cites>FETCH-LOGICAL-c500t-16b504ad5c0a03bdee1e380b8af918928959fbe8a6151d6b83ee4bcb69d52e8c3</cites><orcidid>0000-0002-6897-1626</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00382-022-06557-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00382-022-06557-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Zheng, Fei</creatorcontrib><creatorcontrib>Ren, Haolan</creatorcontrib><creatorcontrib>Lin, Renping</creatorcontrib><creatorcontrib>Zhu, Jiang</creatorcontrib><title>Realistic ocean initial condition for stimulating the successful prediction of extreme cold events in the 2020/2021 winter</title><title>Climate dynamics</title><addtitle>Clim Dyn</addtitle><description>In the first half of winter 2020/2021, several unprecedented cold events occurred in most parts of China and caused record-breaking low temperatures in many cities. However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first evaluated the short-term climate prediction skills in winter of the CAS-ESM-c global coupled model and revealed the key dynamic processes of the onset and development of 2020/2021 extreme cold events based on the ensemble forecasts starting on October 1st, 2020. Under the background provided by the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña), the model captured the abnormal meridional atmospheric pattern well, including the intensification of the Ural Blocking High and the negative phase of the Arctic Oscillation, forecasted the negative geopotential height anomalies over the Eastern Asian region, and finally, successfully predicted the outbreak of cold waves in December 2020 two months in advance. Moreover, the dominant differences in the initial ocean fields between the best and the worst forecast members were further compared to isolate the triggering factor for predicting cold events by CAS-ESM-c. The initial warm sea surface temperature over the Barents Sea can gradually form a meridional pattern between the warm Arctic and the cold Asian continent, which could lead to a reduction in the large-scale meridional temperature gradient at mid-high latitudes and weaken the atmospheric baroclinicity with more conducive to the southward outbreak of cold waves, highlighting that realistic Arctic ocean conditions in autumn can be reasonably assimilated into coupled models to stimulate the successful prediction of extreme cold events in the 2020/2021 winter.</description><subject>Analysis</subject><subject>Anomalies</subject><subject>Arctic Ocean</subject><subject>Arctic Oscillation</subject><subject>Arctic region</subject><subject>Atmospheric models</subject><subject>autumn</subject><subject>Barents Sea</subject><subject>Baroclinic mode</subject><subject>Baroclinity</subject><subject>Blocking anticyclones</subject><subject>China</subject><subject>Climate models</subject><subject>Climate prediction</subject><subject>Climatology</subject><subject>Cold</subject><subject>Cold waves</subject><subject>Cold weather</subject><subject>Dynamic height</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>El Nino phenomena</subject><subject>Ensemble forecasting</subject><subject>Environmental aspects</subject><subject>evolution</subject><subject>Extreme cold</subject><subject>Extreme low temperatures</subject><subject>Extreme weather</subject><subject>Geophysics/Geodesy</subject><subject>Geopotential</subject><subject>Geopotential height</subject><subject>Height anomalies</subject><subject>La Nina</subject><subject>Low temperature</subject><subject>Mathematical models</subject><subject>Oceanography</subject><subject>Oceans</subject><subject>Outbreaks</subject><subject>prediction</subject><subject>Sea surface</subject><subject>Sea surface temperature</subject><subject>Surface temperature</subject><subject>surface water temperature</subject><subject>synergism</subject><subject>Synergistic effect</subject><subject>Temperature gradients</subject><subject>Ural blocking</subject><subject>Weather 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first half of winter 2020/2021, several unprecedented cold events occurred in most parts of China and caused record-breaking low temperatures in many cities. However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first evaluated the short-term climate prediction skills in winter of the CAS-ESM-c global coupled model and revealed the key dynamic processes of the onset and development of 2020/2021 extreme cold events based on the ensemble forecasts starting on October 1st, 2020. Under the background provided by the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña), the model captured the abnormal meridional atmospheric pattern well, including the intensification of the Ural Blocking High and the negative phase of the Arctic Oscillation, forecasted the negative geopotential height anomalies over the Eastern Asian region, and finally, successfully predicted the outbreak of cold waves in December 2020 two months in advance. Moreover, the dominant differences in the initial ocean fields between the best and the worst forecast members were further compared to isolate the triggering factor for predicting cold events by CAS-ESM-c. The initial warm sea surface temperature over the Barents Sea can gradually form a meridional pattern between the warm Arctic and the cold Asian continent, which could lead to a reduction in the large-scale meridional temperature gradient at mid-high latitudes and weaken the atmospheric baroclinicity with more conducive to the southward outbreak of cold waves, highlighting that realistic Arctic ocean conditions in autumn can be reasonably assimilated into coupled models to stimulate the successful prediction of extreme cold events in the 2020/2021 winter.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00382-022-06557-x</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-6897-1626</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Anomalies Arctic Ocean Arctic Oscillation Arctic region Atmospheric models autumn Barents Sea Baroclinic mode Baroclinity Blocking anticyclones China Climate models Climate prediction Climatology Cold Cold waves Cold weather Dynamic height Earth and Environmental Science Earth Sciences El Nino phenomena Ensemble forecasting Environmental aspects evolution Extreme cold Extreme low temperatures Extreme weather Geophysics/Geodesy Geopotential Geopotential height Height anomalies La Nina Low temperature Mathematical models Oceanography Oceans Outbreaks prediction Sea surface Sea surface temperature Surface temperature surface water temperature synergism Synergistic effect Temperature gradients Ural blocking Weather forecasting Winter |
title | Realistic ocean initial condition for stimulating the successful prediction of extreme cold events in the 2020/2021 winter |
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