马登–朱利安振荡(Madden-Julian Oscillation,MJO)作为热带季节内变率的主要模态,其准确预测对于提升次季节预测能力至关重要。然而,MJO具有多尺度演变特征和高度非线性动力过程,现有预测方法在捕捉其复杂时空结构方面仍存在不足。为此...马登–朱利安振荡(Madden-Julian Oscillation,MJO)作为热带季节内变率的主要模态,其准确预测对于提升次季节预测能力至关重要。然而,MJO具有多尺度演变特征和高度非线性动力过程,现有预测方法在捕捉其复杂时空结构方面仍存在不足。为此,本文提出了一种融合多模态数据与时空特征的MJO预测模型(Multimodal data and Integrated Spatiotemporal features for MJO prediction,MISM)。该模型以历史实时多变量MJO指数(Real-time Multivariate MJO index,RMM)和多个气象因子作为联合输入,通过压缩激励模块、卷积模块和Swin Transformer模块构建空间特征提取模块,并引入自回归注意力机制实现非线性时间序列建模。实验结果表明,MISM模型的预测技巧可延伸至30 d以上,并在25 d以上的长期预测阶段表现优于传统的动力学和统计学方法。此外,本文利用显著性图对气象因子贡献区域进行分析,结果显示西太平洋及印尼群岛在不同提前期均呈现较高敏感性,海洋区域贡献普遍强于陆地。水汽和海温异常在短期与中期作用更突出,而低层风场和对流活动在长期阶段贡献较强,高层环流则在各时效保持稳定影响,体现了模型对MJO演变机制的识别能力。展开更多
Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasona...Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasonal precipitation anomalies during summer in China and reveals the contributions of possible driving factors.The results suggest that while single-model ensembles(SMEs)exhibit constrained predictive skills within a limited forecast lead time of three pentads,the MME illustrates an enhanced predictive skill at a lead time of up to four pentads,and even six pentads,in southern China.Based on both deterministic and probabilistic verification metrics,the MME consistently outperforms SMEs,with a more evident advantage observed in probabilistic forecasting.The superior performance of the MME is primarily attributable to the increase in ensemble size,and the enhanced model diversity is also a contributing factor.The reliability of probabilistic skill is largely improved due to the increase in ensemble members,while the resolution term does not exhibit consistent improvement.Furthermore,the Madden–Julian Oscillation(MJO)is revealed as the primary driving factor for the successful prediction of summer precipitation in China using the MME.The improvement by the MME is not solely attributable to the enhancement in the inherent predictive capacity of the MJO itself,but derives from its capability in capturing the more realistic relationship between the MJO and subseasonal precipitation anomalies in China.This study establishes a scientific foundation for acknowledging the advantageous predictive capability of the MME approach in subseasonal predictions of summer precipitation in China,and sheds light on further improving S2S predictions.展开更多
In this study,the Betts-Miller-Janjic(BMJ)convective adjustment scheme in the Weather Research and Forecasting(WRF)model version 4.0 was used to investigate the effect of itsα-parameter,which influences the first-gue...In this study,the Betts-Miller-Janjic(BMJ)convective adjustment scheme in the Weather Research and Forecasting(WRF)model version 4.0 was used to investigate the effect of itsα-parameter,which influences the first-guess potential temperature reference profile on the Madden-Julian oscillation(MJO)propagation and structure.This study diagnosed the MJO active phase composites of the MJO-filtered outgoing longwave radiation(OLR)during the December-to-February(DJF)period of 2006-2016 over the Indian Ocean(IO),Maritime Continent(MC),and western Pacific(WP).The results show that the MJO-filtered OLR intensity,propagation pattern,and MJO classification(standing,jumping,and propagating clusters)are sensitive to theα-value,but the phase speeds of propagating MJOs are not.Overall,with an increasingα-value,the simulated MJO-filtered OLR intensity increases,and the simulated propagation pattern is improved.Results also show that the intensity and propagation pattern of an eastward-propagating MJO are associated with MJO circulation structures and thermodynamic structures.Asαincreases,the front Walker cell and the low-level easterly anomaly are enhanced,which premoistens the lower troposphere and triggers more active shallow and congestus clouds.The enhanced shallow and congestus convection preconditions the lower to middle troposphere,accelerating the transition from congestus to deep convection,thereby facilitating eastward propagation of the MJO.Therefore,the simulated MJO tends to transfer from standing to eastward propagating asαincreases.In summary,increasing theα-value is a possible way to improve the simulation of the structure and propagation of the MJO.展开更多
文摘马登–朱利安振荡(Madden-Julian Oscillation,MJO)作为热带季节内变率的主要模态,其准确预测对于提升次季节预测能力至关重要。然而,MJO具有多尺度演变特征和高度非线性动力过程,现有预测方法在捕捉其复杂时空结构方面仍存在不足。为此,本文提出了一种融合多模态数据与时空特征的MJO预测模型(Multimodal data and Integrated Spatiotemporal features for MJO prediction,MISM)。该模型以历史实时多变量MJO指数(Real-time Multivariate MJO index,RMM)和多个气象因子作为联合输入,通过压缩激励模块、卷积模块和Swin Transformer模块构建空间特征提取模块,并引入自回归注意力机制实现非线性时间序列建模。实验结果表明,MISM模型的预测技巧可延伸至30 d以上,并在25 d以上的长期预测阶段表现优于传统的动力学和统计学方法。此外,本文利用显著性图对气象因子贡献区域进行分析,结果显示西太平洋及印尼群岛在不同提前期均呈现较高敏感性,海洋区域贡献普遍强于陆地。水汽和海温异常在短期与中期作用更突出,而低层风场和对流活动在长期阶段贡献较强,高层环流则在各时效保持稳定影响,体现了模型对MJO演变机制的识别能力。
基金sponsored by the National Natural Science Foundation of China(Grant Nos.42175052 and U2442206)the Joint Research Project for Meteorological Capacity Improvement(Grant No.23NLTSQ007,23NLTSZ003)+2 种基金the Innovative Development Special Project of the China Meteorological Administration(Grant No.CXFZ2023J002)the National Key R&D Program of China(Grant No.2023YFC3007700,2024YFC3013100)the China Meteorological Administration Youth Innovation Team(Grant No.CMA2024QN06)。
文摘Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasonal precipitation anomalies during summer in China and reveals the contributions of possible driving factors.The results suggest that while single-model ensembles(SMEs)exhibit constrained predictive skills within a limited forecast lead time of three pentads,the MME illustrates an enhanced predictive skill at a lead time of up to four pentads,and even six pentads,in southern China.Based on both deterministic and probabilistic verification metrics,the MME consistently outperforms SMEs,with a more evident advantage observed in probabilistic forecasting.The superior performance of the MME is primarily attributable to the increase in ensemble size,and the enhanced model diversity is also a contributing factor.The reliability of probabilistic skill is largely improved due to the increase in ensemble members,while the resolution term does not exhibit consistent improvement.Furthermore,the Madden–Julian Oscillation(MJO)is revealed as the primary driving factor for the successful prediction of summer precipitation in China using the MME.The improvement by the MME is not solely attributable to the enhancement in the inherent predictive capacity of the MJO itself,but derives from its capability in capturing the more realistic relationship between the MJO and subseasonal precipitation anomalies in China.This study establishes a scientific foundation for acknowledging the advantageous predictive capability of the MME approach in subseasonal predictions of summer precipitation in China,and sheds light on further improving S2S predictions.
基金supported by the National Natural Science Foundation of China(Grant Nos.41975090,U2242201,42075077)the Natural Science Foundation of Hunan Province,China(2022JJ20043)the Science and Technology Innovation Program of Hunan Province,China(2022RC1239)。
文摘In this study,the Betts-Miller-Janjic(BMJ)convective adjustment scheme in the Weather Research and Forecasting(WRF)model version 4.0 was used to investigate the effect of itsα-parameter,which influences the first-guess potential temperature reference profile on the Madden-Julian oscillation(MJO)propagation and structure.This study diagnosed the MJO active phase composites of the MJO-filtered outgoing longwave radiation(OLR)during the December-to-February(DJF)period of 2006-2016 over the Indian Ocean(IO),Maritime Continent(MC),and western Pacific(WP).The results show that the MJO-filtered OLR intensity,propagation pattern,and MJO classification(standing,jumping,and propagating clusters)are sensitive to theα-value,but the phase speeds of propagating MJOs are not.Overall,with an increasingα-value,the simulated MJO-filtered OLR intensity increases,and the simulated propagation pattern is improved.Results also show that the intensity and propagation pattern of an eastward-propagating MJO are associated with MJO circulation structures and thermodynamic structures.Asαincreases,the front Walker cell and the low-level easterly anomaly are enhanced,which premoistens the lower troposphere and triggers more active shallow and congestus clouds.The enhanced shallow and congestus convection preconditions the lower to middle troposphere,accelerating the transition from congestus to deep convection,thereby facilitating eastward propagation of the MJO.Therefore,the simulated MJO tends to transfer from standing to eastward propagating asαincreases.In summary,increasing theα-value is a possible way to improve the simulation of the structure and propagation of the MJO.
基金China National 973 project(2015CB453200)China National project(41575070)+7 种基金NSFC(41475084)OLR(N00014-16-12260)NRL(N00173-13-1-G902)Jiangsu NSF Key Project(BK20150062)Jiangsu Shuang-Chuang Team(R2014SCT001)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)China Special Fund for Meteorological Research in the Public Interest(GYHY201306028)Colleges and Universities in Jiangsu Province Plans to Graduate Research and Innovation(CXLX13_486)
