%0 Journal Article %1 jie2017simulations %A Jie, Weihua %A Vitart, Frederic %A Wu, Tongwen %A Liu, Xiangwen %D 2017 %J Quarterly Journal of the Royal Meteorological Society %K eastasianmonsoon monthly seasonal skill China %N 706 %P 2282-2295 %R 10.1002/qj.3085 %T Simulations of Asian Summer Monsoon in the Sub-seasonal to Seasonal Prediction Project (S2S) database %V 143 %X Several monsoon indices have been applied to multiple models from the sub‐seasonal to seasonal (S2S) prediction project database during the period May to October 1999–2010 to assess their ability to simulate the Asian monsoon. The bivariate anomaly correlation (BAC) of the Boreal Summer IntraSeasonal Oscillation (BSISO) index suggests that the operational models can predict the BSISO1 and BSISO2 events up to 6–24.5 and 6.5–14 days in advance respectively, although the models tend to underestimate the amplitude of BSISO as the lead time increases. For the strong BSISO events, BSISO1 (BSISO2) display lower skill mostly in phases 3–5 for all the models, suggesting that the BSISO1 (BSISO2) is not easy to predict when it is located over India and the Maritime Continent (South China Sea and Bay of Bengal). On the other hand, the higher skills appear in different phases for different models. For instance, the limit of predictive skill of strong BSISO1 and BSISO2 events in phases 6–7 for the ECMWF ensemble forecast could exceed 30 and 28 days, respectively. The comparisons of the BSISO life cycle among the ECMWF, NCEP and CMA models also indicate that the ECMWF model can better predict the evolution of strong BSISO events. Predictions of additional monsoon circulation indices including the Webster–Yang index (WY), Indian Summer Monsoon index (ISM), South Asian Monsoon index (SAM), and SouthEast Asian Monsoon index (SEAM) in the S2S models have statistically significant skill over the corresponding monsoon regions up to 9–31, 3–17, 7–13 and 7–14 days, respectively. However, the significant skill of summer monsoon precipitation over the SAM and SEAM regions varies significantly among the models, with the skill ranging from 2 days to 2 weeks lead time.

@article{jie2017simulations, abstract = {Several monsoon indices have been applied to multiple models from the sub‐seasonal to seasonal (S2S) prediction project database during the period May to October 1999–2010 to assess their ability to simulate the Asian monsoon. The bivariate anomaly correlation (BAC) of the Boreal Summer IntraSeasonal Oscillation (BSISO) index suggests that the operational models can predict the BSISO1 and BSISO2 events up to 6–24.5 and 6.5–14 days in advance respectively, although the models tend to underestimate the amplitude of BSISO as the lead time increases. For the strong BSISO events, BSISO1 (BSISO2) display lower skill mostly in phases 3–5 for all the models, suggesting that the BSISO1 (BSISO2) is not easy to predict when it is located over India and the Maritime Continent (South China Sea and Bay of Bengal). On the other hand, the higher skills appear in different phases for different models. For instance, the limit of predictive skill of strong BSISO1 and BSISO2 events in phases 6–7 for the ECMWF ensemble forecast could exceed 30 and 28 days, respectively. The comparisons of the BSISO life cycle among the ECMWF, NCEP and CMA models also indicate that the ECMWF model can better predict the evolution of strong BSISO events. Predictions of additional monsoon circulation indices including the Webster–Yang index (WY), Indian Summer Monsoon index (ISM), South Asian Monsoon index (SAM), and SouthEast Asian Monsoon index (SEAM) in the S2S models have statistically significant skill over the corresponding monsoon regions up to 9–31, 3–17, 7–13 and 7–14 days, respectively. However, the significant skill of summer monsoon precipitation over the SAM and SEAM regions varies significantly among the models, with the skill ranging from 2 days to 2 weeks lead time. }, added-at = {2018-06-22T09:05:03.000+0200}, author = {Jie, Weihua and Vitart, Frederic and Wu, Tongwen and Liu, Xiangwen}, biburl = {https://www.bibsonomy.org/bibtex/260505fa079314b518bb9c3f432a0b8e1/pbett}, doi = {10.1002/qj.3085}, interhash = {68132a1c888c08210e2ed08db8814d3c}, intrahash = {60505fa079314b518bb9c3f432a0b8e1}, journal = { Quarterly Journal of the Royal Meteorological Society}, keywords = {eastasianmonsoon monthly seasonal skill China}, month = jul, number = 706, pages = {2282-2295}, timestamp = {2018-08-22T09:32:01.000+0200}, title = {Simulations of Asian Summer Monsoon in the Sub-seasonal to Seasonal Prediction Project (S2S) database}, volume = 143, year = 2017 }