Seasonal predictability of summer north african subtropical high in operational climate prediction models
Seasonal predictability of summer North African Subtropical High (NASH) is investigated in this study by utilizing the hindcast data from four operational climate prediction models, including BCC_CSM1.1(m), NCEP CFSv2, ECMWF System 4, and JMA CPSv2. By reconstructing indices describing the variation...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2023-01-01
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| Series: | Environmental Research Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2515-7620/acf36b |
| _version_ | 1797692987718762496 |
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| author | Fang Zhou Ali Said Juma Ran Zi Jian Shi Ming-Hong Liu |
| author_facet | Fang Zhou Ali Said Juma Ran Zi Jian Shi Ming-Hong Liu |
| author_sort | Fang Zhou |
| collection | DOAJ |
| description | Seasonal predictability of summer North African Subtropical High (NASH) is investigated in this study by utilizing the hindcast data from four operational climate prediction models, including BCC_CSM1.1(m), NCEP CFSv2, ECMWF System 4, and JMA CPSv2. By reconstructing indices describing the variations in intensity, area, eastern boundary and ridge line of the NASH, it is shown that the intensity and area indices present high prediction skills compared to the relatively low prediction skills of position indices. The multi-model ensemble (MME) mean, calculated as the arithmetic average of the four models, presents relatively higher and stabler skills than individual models. Further investigation indicates that the prediction skill of the NASH is largely reliant on the models’ ability in reproducing the relationship between the NASH indices and the tropical-to-subtropical sea surface temperature (SST) anomalies associated with the El Niño/Southern Oscillation (ENSO). The pattern of atmospheric circulation anomaly over the North Africa in response to ENSO is well captured by the models, which suggests the dominant source of predictability of the NASH. |
| first_indexed | 2024-03-12T02:37:02Z |
| format | Article |
| id | doaj.art-23770b17cbf14d4385587851b1507699 |
| institution | Directory Open Access Journal |
| issn | 2515-7620 |
| language | English |
| last_indexed | 2024-03-12T02:37:02Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Communications |
| spelling | doaj.art-23770b17cbf14d4385587851b15076992023-09-04T14:15:23ZengIOP PublishingEnvironmental Research Communications2515-76202023-01-015909100110.1088/2515-7620/acf36bSeasonal predictability of summer north african subtropical high in operational climate prediction modelsFang Zhou0https://orcid.org/0000-0002-6059-0108Ali Said Juma1Ran Zi2Jian Shi3Ming-Hong Liu4Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of ChinaMeteorological Bureau of Xishuangbanna Prefecture, Jinghong 666100, People’s Republic of ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of ChinaState Key Laboratory of Severe Weather/Institute of Tibetan Plateau Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, People’s Republic of ChinaSeasonal predictability of summer North African Subtropical High (NASH) is investigated in this study by utilizing the hindcast data from four operational climate prediction models, including BCC_CSM1.1(m), NCEP CFSv2, ECMWF System 4, and JMA CPSv2. By reconstructing indices describing the variations in intensity, area, eastern boundary and ridge line of the NASH, it is shown that the intensity and area indices present high prediction skills compared to the relatively low prediction skills of position indices. The multi-model ensemble (MME) mean, calculated as the arithmetic average of the four models, presents relatively higher and stabler skills than individual models. Further investigation indicates that the prediction skill of the NASH is largely reliant on the models’ ability in reproducing the relationship between the NASH indices and the tropical-to-subtropical sea surface temperature (SST) anomalies associated with the El Niño/Southern Oscillation (ENSO). The pattern of atmospheric circulation anomaly over the North Africa in response to ENSO is well captured by the models, which suggests the dominant source of predictability of the NASH.https://doi.org/10.1088/2515-7620/acf36bsummer north african subtropical highseasonal predictabilityoperational climate prediction modelsENSO |
| spellingShingle | Fang Zhou Ali Said Juma Ran Zi Jian Shi Ming-Hong Liu Seasonal predictability of summer north african subtropical high in operational climate prediction models Environmental Research Communications summer north african subtropical high seasonal predictability operational climate prediction models ENSO |
| title | Seasonal predictability of summer north african subtropical high in operational climate prediction models |
| title_full | Seasonal predictability of summer north african subtropical high in operational climate prediction models |
| title_fullStr | Seasonal predictability of summer north african subtropical high in operational climate prediction models |
| title_full_unstemmed | Seasonal predictability of summer north african subtropical high in operational climate prediction models |
| title_short | Seasonal predictability of summer north african subtropical high in operational climate prediction models |
| title_sort | seasonal predictability of summer north african subtropical high in operational climate prediction models |
| topic | summer north african subtropical high seasonal predictability operational climate prediction models ENSO |
| url | https://doi.org/10.1088/2515-7620/acf36b |
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