摘要
The Madden–Julian Oscillation(MJO)has a significant impact on global weather and climate and can be used as a predictability resource in extended-term forecasting.We evaluate the ability of the Chinese Academy of Meteorological Sciences Climate System Model(CAMS-CSM)to represent the MJO by using the diagnostic method proposed by the US Climate Variability and Predictability Program(CLIVAR)MJO Working Group(MJOWG).In general,the model simulates some major characteristics of MJO well,such as the seasonality characteristics and geographical dependence,the intensity of intraseasonal variability(ISV),dominant periodicity,propagation characteristics,coherence between outgoing longwave radiation(OLR)and wind,and life cycle of MJO signals.However,there are a few biases in the model when compared with observational/reanalyzed data.These include an overestimate of precipitation in the convergence zone of the North and South Pacific,a slightly weaker eastward propagation,and a shift in the dominant periodicity toward lower frequencies with slower speeds of eastward propagation.The model gives a poor simulation of the northward propagation of MJO in summer and shows less coherence between the MJO convection and wind.The role of moistening in the planetary boundary layer(PBL)in the eastward/northward propagation of MJO was also explored.An accurate representation of the vertical titling structure of moisture anomalies in CAMS-CSM leads to moistening of the PBL ahead of convection,which accounts for the eastward/northward propagation of MJO.Poor simulation of the vertical structure of the wind and moisture anomalies in the western Pacific leads to a poor simulation of the northward propagation of MJO in this area.Budget analysis of the PBL integral moisture anomalies shows that the model gives a good simulation of the moisture charging process ahead of MJO convection and that the zonal advection of moisture convergence term has a primary role in the detour of MJO over the Maritime Continent.
The Madden–Julian Oscillation(MJO) has a significant impact on global weather and climate and can be used as a predictability resource in extended-term forecasting. We evaluate the ability of the Chinese Academy of Meteorological Sciences Climate System Model(CAMS-CSM) to represent the MJO by using the diagnostic method proposed by the US Climate Variability and Predictability Program(CLIVAR) MJO Working Group(MJOWG). In general,the model simulates some major characteristics of MJO well, such as the seasonality characteristics and geographical dependence, the intensity of intraseasonal variability(ISV), dominant periodicity, propagation characteristics, coherence between outgoing longwave radiation(OLR) and wind, and life cycle of MJO signals. However, there are a few biases in the model when compared with observational/reanalyzed data. These include an overestimate of precipitation in the convergence zone of the North and South Pacific, a slightly weaker eastward propagation, and a shift in the dominant periodicity toward lower frequencies with slower speeds of eastward propagation. The model gives a poor simulation of the northward propagation of MJO in summer and shows less coherence between the MJO convection and wind. The role of moistening in the planetary boundary layer(PBL) in the eastward/northward propagation of MJO was also explored. An accurate representation of the vertical titling structure of moisture anomalies in CAMS-CSM leads to moistening of the PBL ahead of convection, which accounts for the eastward/northward propagation of MJO. Poor simulation of the vertical structure of the wind and moisture anomalies in the western Pacific leads to a poor simulation of the northward propagation of MJO in this area. Budget analysis of the PBL integral moisture anomalies shows that the model gives a good simulation of the moisture charging process ahead of MJO convection and that the zonal advection of moisture convergence term has a primary role in the detour of MJO over the Maritime Continent.
基金
Supported by the National Key Research and Development Program of China(2018YFC1505906)
National Basic Research(973)Program of China(2015CB453203 and 2010CB950404)
National Natural Science Foundation of China(41505065,41375062,and41775066)
China Meteorological Administration Special Public Welfare Research Fund(GYHY201406022)
