The skill of atmospheric linear inverse models in hindcasting the Madden-Julian Oscillation

被引：23

作者：

Cavanaugh, Nicholas R. ^{[1
]}

Allen, Teddy ^{[2
]}

Subramanian, Aneesh ^{[1
]}

Mapes, Brian ^{[2
]}

Seo, Hyodae ^{[3
]}

Miller, Arthur J. ^{[1
]}

机构：

[1] Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92093 USA

[2] Univ Miami, Rosenstiel Sch Marine & Atmospher Sci, Miami, FL 33149 USA

[3] MIT, Woods Hole Oceanog Inst, Woods Hole, MA USA

来源：

CLIMATE DYNAMICS | 2015年 / 44卷 / 3-4期

基金：

美国国家科学基金会;

关键词：

Madden-Julian Oscillation; Hindcast; Predictability; Linear inverse model; Tropical dynamics; OUTGOING LONGWAVE RADIATION; STATISTICAL FORECAST MODEL; EXTENDED-RANGE PREDICTION; SEA-SURFACE TEMPERATURES; MULTIVARIATE MJO INDEX; PATTERN-ANALYSIS; VARIABILITY; PREDICTABILITY; HEMISPHERE; ENSO;

D O I：

10.1007/s00382-014-2181-x

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

A suite of statistical atmosphere-only linear inverse models of varying complexity are used to hindcast recent MJO events from the Year of Tropical Convection and the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the Madden-Julian Oscillation mission periods, as well as over the 2000-2009 time period. Skill exists for over two weeks, competitive with the skill of some numerical models in both bivariate correlation and root-mean-squared-error scores during both observational mission periods. Skill is higher during mature Madden-Julian Oscillation conditions, as opposed to during growth phases, suggesting that growth dynamics may be more complex or non-linear since they are not as well captured by a linear model. There is little prediction skill gained by including non-leading modes of variability.

引用

页码：897 / 906

页数：10

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