The influence of single model ensemble on the simulated extratropical interannual variability
This study compares the interannual variance of boreal winter near-surface temperature (DJF T2m) with and without performing single model ensemble (SME) in seasonal hindcasts (DEMETER, ENSEMBLES, and NCEP CFSv2) and historical climate simulations (CMIP5). The results demonstrate that the extratropic...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2018-01-01
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| Series: | Terrestrial, Atmospheric and Oceanic Sciences |
| Online Access: |
http://tao.cgu.org.tw/media/k2/attachments/v296p679.pdf
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| _version_ | 1817978068135837696 |
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| author | Chia-Chi Wang Huang-Hsiung Hsu Yu-Luen Chen Jun-Kai Yang Meng-Pai Hung |
| author_facet | Chia-Chi Wang Huang-Hsiung Hsu Yu-Luen Chen Jun-Kai Yang Meng-Pai Hung |
| author_sort | Chia-Chi Wang |
| collection | DOAJ |
| description | This study compares the interannual variance of boreal winter near-surface temperature (DJF T2m) with and without performing single model ensemble (SME) in seasonal hindcasts (DEMETER, ENSEMBLES, and NCEP CFSv2) and historical climate simulations (CMIP5). The results demonstrate that the extratropical temperature variability is significantly reduced after performing SME even though the signal in the tropical Pacific remains strong. Cancellation between positive and negative perturbations simulated by individual model members, of both tropical and extratropical origins, leads to the under-simulation. The atmospheric circulation induced by tropical Pacific sea surface temperature is not well represented in global climate models and the simulation is further deteriorated by SME, leading to an unrealistically weak interannual variance of simulated winter temperature in North America. Similar effect was also found in North Eurasia where winter temperature is strongly influenced by atmospheric internal variability and its interaction with land and ice/snow in the middle-high latitudes. The SME procedure should be avoided when evaluating the model performance in simulating the higher-order long-term statistics (such as variance). Variance of individual models should be calculated first and then averaged among members. Models used in seasonal forecast and long-term climate simulation already have good capability in simulating the long-term statistics of stochastic processes in the extratropics, although the capability in accurately simulating the temporal variation is still poor. |
| first_indexed | 2024-04-13T22:24:25Z |
| format | Article |
| id | doaj.art-1bd72c235656439f94c7ee15d3e29de6 |
| institution | Directory Open Access Journal |
| issn | 1017-0839 2311-7680 |
| language | English |
| last_indexed | 2024-04-13T22:24:25Z |
| publishDate | 2018-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Terrestrial, Atmospheric and Oceanic Sciences |
| spelling | doaj.art-1bd72c235656439f94c7ee15d3e29de62022-12-22T02:27:06ZengSpringerTerrestrial, Atmospheric and Oceanic Sciences1017-08392311-76802018-01-0129667969410.3319/TAO.2018.07.18.01The influence of single model ensemble on the simulated extratropical interannual variabilityChia-Chi WangHuang-Hsiung HsuYu-Luen ChenJun-Kai YangMeng-Pai HungThis study compares the interannual variance of boreal winter near-surface temperature (DJF T2m) with and without performing single model ensemble (SME) in seasonal hindcasts (DEMETER, ENSEMBLES, and NCEP CFSv2) and historical climate simulations (CMIP5). The results demonstrate that the extratropical temperature variability is significantly reduced after performing SME even though the signal in the tropical Pacific remains strong. Cancellation between positive and negative perturbations simulated by individual model members, of both tropical and extratropical origins, leads to the under-simulation. The atmospheric circulation induced by tropical Pacific sea surface temperature is not well represented in global climate models and the simulation is further deteriorated by SME, leading to an unrealistically weak interannual variance of simulated winter temperature in North America. Similar effect was also found in North Eurasia where winter temperature is strongly influenced by atmospheric internal variability and its interaction with land and ice/snow in the middle-high latitudes. The SME procedure should be avoided when evaluating the model performance in simulating the higher-order long-term statistics (such as variance). Variance of individual models should be calculated first and then averaged among members. Models used in seasonal forecast and long-term climate simulation already have good capability in simulating the long-term statistics of stochastic processes in the extratropics, although the capability in accurately simulating the temporal variation is still poor. http://tao.cgu.org.tw/media/k2/attachments/v296p679.pdf |
| spellingShingle | Chia-Chi Wang Huang-Hsiung Hsu Yu-Luen Chen Jun-Kai Yang Meng-Pai Hung The influence of single model ensemble on the simulated extratropical interannual variability Terrestrial, Atmospheric and Oceanic Sciences |
| title | The influence of single model ensemble on the simulated extratropical interannual variability |
| title_full | The influence of single model ensemble on the simulated extratropical interannual variability |
| title_fullStr | The influence of single model ensemble on the simulated extratropical interannual variability |
| title_full_unstemmed | The influence of single model ensemble on the simulated extratropical interannual variability |
| title_short | The influence of single model ensemble on the simulated extratropical interannual variability |
| title_sort | influence of single model ensemble on the simulated extratropical interannual variability |
| url |
http://tao.cgu.org.tw/media/k2/attachments/v296p679.pdf
|
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