Further Study on identifying Anomalous Large-Scale Rainfall Regimes in Phase Space
Using a 40-yr dally precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China are investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data,...
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Published in | Acta meteorologica Sinica Vol. 20; no. 1; pp. 62 - 71 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
Beijing
Springer Nature B.V
2006
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000%National Meteorological Centre, Beijing 100081%Laboratory for Climate Studies of China Meteorological Administration, National Climate Centre, Beijing 100081 Laboratory for Climate Studies of China Meteorological Administration, National Climate Centre, Beijing 100081 |
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Abstract | Using a 40-yr dally precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China are investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data, the six rainfall regimes (RRs) are identified by applying a cluster analysis method, namely, the northeastern China regime, Yellow River regime, Qinling Mountain-Hualhe River regime, Yangtze River with its south regime, South China regime, and rainless regime. Analyses show that the new RRs exhibit good persistence and evident physical sense, and excellently represent both of countrywide and regional features, which also demonstrate the inhomogeneity of multi-dimensional phase space. ~rthermore, it is more important that the new RRs can describe intraseasonal dynamic characteristics of large-scale rainfall anomalies, which is the most significant difference between the new RRs and the conventional seasonal mean rainfall patterns. On the other hand, the climatic characteristics of dally distributions of the RRs events, as well as the 40-year panorama of the RRs occurring are also investigated, which further document rationality and objectivity of the RRs with intraseasonal variability, and are likely to present more helpful information for short-term climate prediction, compared with other previous classical rainfall patterns. |
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AbstractList | Using a 40-yr dally precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China are investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data, the six rainfall regimes (RRs) are identified by applying a cluster analysis method, namely, the northeastern China regime, Yellow River regime, Qinling Mountain-Hualhe River regime, Yangtze River with its south regime, South China regime, and rainless regime. Analyses show that the new RRs exhibit good persistence and evident physical sense, and excellently represent both of countrywide and regional features, which also demonstrate the inhomogeneity of multi-dimensional phase space. ~rthermore, it is more important that the new RRs can describe intraseasonal dynamic characteristics of large-scale rainfall anomalies, which is the most significant difference between the new RRs and the conventional seasonal mean rainfall patterns. On the other hand, the climatic characteristics of dally distributions of the RRs events, as well as the 40-year panorama of the RRs occurring are also investigated, which further document rationality and objectivity of the RRs with intraseasonal variability, and are likely to present more helpful information for short-term climate prediction, compared with other previous classical rainfall patterns. P4; Using a 40-yr daily precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China are investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data, the six rainfall regimes (RRs) are identified by applying a cluster analysis method, namely, the northeastern China regime,Yellow River regime, Qinling Mountain-Huaihe River regime, Yangtze River with its south regime, South China regime, and rainless regime. Analyses show that the new RRs exhibit good persistence and evident physical sense, and excellently represent both of countrywide and regional features, which also demonstrate the inhomogeneity of multi-dimensional phase space. Furthermore, it is more important that the new RRs can describe intraseasonal dynamic characteristics of large-scale rainfall anomalies, which is the most significant difference between the new RRs and the conventional seasonal mean rainfall patterns. On the other hand, the climatic characteristics of daily distributions of the RRs events, as well as the 40-year panorama of the RRs occurring are also investigated, which further document rationality and objectivity of the RRs with intraseasonal variability, and are likely to present more helpful information for short-term climate prediction,compared with other previous classical rainfall patterns. Using a 40-yr daily precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China are investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data, the six rainfall regimes (RRs) are identified by applying a cluster analysis method, namely, the northeastern China regime, Yellow River regime, Qinling Mountain-Huaihe River regime, Yangtze River with its south regime, South China regime, and rainless regime. Analyses show that the new RRs exhibit good persistence and evident physical sense, and excellently represent both of countrywide and regional features, which also demonstrate the inhomogeneity of multi-dimensional phase space. Furthermore, it is more important that the new RRs can describe intraseasonal dynamic characteristics of large-scale rainfall anomalies, which is the most significant difference between the new RRs and the conventional seasonal mean rainfall patterns. On the other hand, the climatic characteristics of daily distributions of the RRs events, as well as the 40-year panorama of the RRs occurring are also investigated, which further document rationality and objectivity of the RRs with intraseasonal variability, and are likely to present more helpful information for short-term climate prediction, compared with other previous classical rainfall patterns. Using a 40-yr daily precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China axe investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data, the six rainfall regimes (RRs) are identified by applying a cluster analysis method, namely, the northeastern China regime, Yellow River regime, Qinling Mountain-Huaihe River regime, Yangtze River with its south regime, South China regime, and rainless regime. Analyses show that the new RRs exhibit good persistence and evident physical sense, and excellently represent both of countrywide and regional features, which also demonstrate the inhomogeneity of multi-dimensional phase space. Furthermore, it is more important that the new RRs can describe intraseasonal dynamic characteristics of large-scale rainfall anomalies, which is the most significant difference between the new RRs and the conventional seasonal mean rainfall patterns. On the other hand, the climatic characteristics of daily distributions of the RRs events, as well as the 40-year panorama of the RRs occurring axe also investigated, which further document rationality and objectivity of the RRs with intraseasonal variability, and axe likely to present more helpful information for short-term climate prediction, compared with other previous classical rainfall patterns. [PUBLICATION ABSTRACT] |
Author | 任宏利 高丽 张培群 李维京 |
AuthorAffiliation | Laboratory for Climate Studies of China Meteorological Administration, National Climate Centre, Beijing 100081 National Meteorological Centre, Beijing 100081 College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000 |
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Title | Further Study on identifying Anomalous Large-Scale Rainfall Regimes in Phase Space |
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