2023年春季,我国西南地区发生了严重的气象干旱,对当地社会经济造成严重影响。为深入认识这次干旱事件的成因、并为未来西南地区春旱的预测提供科学依据,本文利用站点观测数据、美国国家环境预测中心和国家大气研究中心(National Center...2023年春季,我国西南地区发生了严重的气象干旱,对当地社会经济造成严重影响。为深入认识这次干旱事件的成因、并为未来西南地区春旱的预测提供科学依据,本文利用站点观测数据、美国国家环境预测中心和国家大气研究中心(National Centers for Environmental Prediction/National Center for Atmospheric Research,NCEP/NCAR)再分析数据、美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)的海表温度等,采用T-N波作用通量和合成分析等方法,从海温和热带大气季节内振荡(Madden-Julian Oscillation,MJO)的角度深入探讨此次春旱成因。结果表明:(1)2023年我国西南春旱是高温干旱复合事件,3月干旱发生在中部,4月干旱加剧并向西扩展,5月干旱持续。(2)3月北太平洋的马蹄形海温异常导致西风急流偏南偏西,抑制了西南地区的降水。(3)4月印度洋暖海温通过Kelvin波导致孟加拉湾附近的反气旋式环流异常,西北太平洋暖海温通过Rossby波导致南海至菲律宾的气旋式环流异常,造成西南地区南部出现偏北风,导致水汽辐散,加剧干旱。(4)5月MJO长时间维持在西太平洋,通过Gill响应引发南海至菲律宾对流层低层的气旋异常,减少偏南水汽的输送,从而使得西南干旱持续。展开更多
As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates th...As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates the models’capability to simulate and predict the Madden-Julian Oscillation(MJO).Three versions of the Beijing Climate Center Climate System Model(BCC-CSM)are used to conduct historical simulations and re-forecast experiments(referred to as EXP1,EXP1-M,and EXP2,respectively).In simulating MJO characteristics,the newly-developed high-resolution BCC-CSM outperforms its predecessors.In terms of MJO prediction,the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M,and further to 24 days in EXP2.Within the first forecast week,the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill.However,during forecast weeks 2–3,EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3.Particularly at initial phases 2–3,EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection,leading to the highest prediction skill of the MJO.Our results reveal that,during the participation of the CMA models in the S2S Project,both the improved model initialization and updated model physics played positive roles in improving MJO prediction.Future efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times.展开更多
文摘2023年春季,我国西南地区发生了严重的气象干旱,对当地社会经济造成严重影响。为深入认识这次干旱事件的成因、并为未来西南地区春旱的预测提供科学依据,本文利用站点观测数据、美国国家环境预测中心和国家大气研究中心(National Centers for Environmental Prediction/National Center for Atmospheric Research,NCEP/NCAR)再分析数据、美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)的海表温度等,采用T-N波作用通量和合成分析等方法,从海温和热带大气季节内振荡(Madden-Julian Oscillation,MJO)的角度深入探讨此次春旱成因。结果表明:(1)2023年我国西南春旱是高温干旱复合事件,3月干旱发生在中部,4月干旱加剧并向西扩展,5月干旱持续。(2)3月北太平洋的马蹄形海温异常导致西风急流偏南偏西,抑制了西南地区的降水。(3)4月印度洋暖海温通过Kelvin波导致孟加拉湾附近的反气旋式环流异常,西北太平洋暖海温通过Rossby波导致南海至菲律宾的气旋式环流异常,造成西南地区南部出现偏北风,导致水汽辐散,加剧干旱。(4)5月MJO长时间维持在西太平洋,通过Gill响应引发南海至菲律宾对流层低层的气旋异常,减少偏南水汽的输送,从而使得西南干旱持续。
基金supported by the National Natural Science Foundation of China(Grant No.42075161).
文摘As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates the models’capability to simulate and predict the Madden-Julian Oscillation(MJO).Three versions of the Beijing Climate Center Climate System Model(BCC-CSM)are used to conduct historical simulations and re-forecast experiments(referred to as EXP1,EXP1-M,and EXP2,respectively).In simulating MJO characteristics,the newly-developed high-resolution BCC-CSM outperforms its predecessors.In terms of MJO prediction,the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M,and further to 24 days in EXP2.Within the first forecast week,the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill.However,during forecast weeks 2–3,EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3.Particularly at initial phases 2–3,EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection,leading to the highest prediction skill of the MJO.Our results reveal that,during the participation of the CMA models in the S2S Project,both the improved model initialization and updated model physics played positive roles in improving MJO prediction.Future efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times.
