Estimate of the Predictability of Boreal Summer and Winter Intraseasonal Oscillations from Observations

被引:78
作者
Ding, Ruiqiang [1 ]
Li, Jianping [1 ]
Seo, Kyong-Hwan [2 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China
[2] Pusan Natl Univ, Dept Atmospher Sci, Pusan, South Korea
关键词
MADDEN-JULIAN OSCILLATION; TROPICAL-EXTRATROPICAL INTERACTION; SEA-SURFACE TEMPERATURE; ATMOSPHERIC PREDICTABILITY; LYAPUNOV EXPONENTS; CIRCULATION MODEL; FORECAST SKILL; VARIABILITY; PREDICTION; LONG;
D O I
10.1175/2011MWR3571.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Tropical intraseasonal variability (TISV) shows two dominant modes: the boreal winter Madden-Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). The two modes differ in intensity, frequency, and movement, thereby presumably indicating different predictabilities. This paper investigates differences in the predictability limits of the BSISO and the boreal winter MJO based on observational data. The results show that the potential predictability limit of the BSISO obtained from bandpass-filtered (30-80 days) outgoing longwave radiation (OLR), 850-hPa winds, and 200-hPa velocity potential is close to 5 weeks, comparable to that of the boreal winter MJO. Despite the similarity between the potential predictability limits of the BSISO and MJO, the spatial distribution of the potential predictability limit of the TISV during summer is very different from that during winter. During summer, the limit is relatively low over regions where the TISV is most active, whereas it is relatively high over the North Pacific, North Atlantic, southern Africa, and South America. The spatial distribution of the limit during winter is approximately the opposite of that during summer. For strong phases of ISO convection, the initial error of the BSISO shows a more rapid growth than that of the MJO. The error growth is rapid when the BSISO and MJO enter the decaying phase (when ISO signals are weak), whereas it is slow when convection anomalies of the BSISO and MJO are located in upstream regions (when ISO signals are strong).
引用
收藏
页码:2421 / 2438
页数:18
相关论文
共 55 条
[1]  
[Anonymous], 1965, Tellus, DOI [DOI 10.1111/J.2153-3490.1965.TB01424.X, DOI 10.3402/TELLUSA.V17I3.9076]
[2]   Nonlinear finite-time Lyapunov exponent and predictability [J].
Ding, Ruiqiang ;
Li, Jianping .
PHYSICS LETTERS A, 2007, 364 (05) :396-400
[3]   Predictability of the Madden-Julian Oscillation Estimated Using Observational Data [J].
Ding, Ruiqiang ;
Li, Jianping ;
Seo, Kyong-Hwan .
MONTHLY WEATHER REVIEW, 2010, 138 (03) :1004-1013
[4]   Trends and interdecadal changes of weather predictability during 1950s-1990s [J].
Ding, Ruiqiang ;
Li, Jianping ;
Ha, Kyung-Ja .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2008, 113
[5]   ERGODIC-THEORY OF CHAOS AND STRANGE ATTRACTORS [J].
ECKMANN, JP ;
RUELLE, D .
REVIEWS OF MODERN PHYSICS, 1985, 57 (03) :617-656
[6]  
FERRANTI L, 1990, J ATMOS SCI, V47, P2177, DOI 10.1175/1520-0469(1990)047<2177:TEIAWT>2.0.CO
[7]  
2
[8]   Impact of atmosphere-ocean coupling on the predictability of monsoon intraseasonal oscillations [J].
Fu, Xiouhua ;
Wang, Bin ;
Waliser, Duane E. ;
Tao, Li .
JOURNAL OF THE ATMOSPHERIC SCIENCES, 2007, 64 (01) :157-174
[9]   Predictability in the Lorenz low-order general atmospheric circulation model [J].
GonzalezMiranda, JM .
PHYSICS LETTERS A, 1997, 233 (4-6) :347-354
[10]  
Hendon HH, 2000, MON WEATHER REV, V128, P69, DOI 10.1175/1520-0493(2000)128<0069:MRFEAW>2.0.CO