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Can reanalysis products with only surface variables assimilated capture Madden–Julian oscillation characteristics?
Author(s) -
Cui Jingxuan,
Wang Lu,
Li Tim,
Wu Bo
Publication year - 2020
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.6270
Subject(s) - madden–julian oscillation , climatology , data assimilation , environmental science , oscillation (cell signaling) , mode (computer interface) , sea surface temperature , general circulation model , meteorology , atmospheric sciences , geology , climate change , convection , geography , computer science , oceanography , biology , genetics , operating system
The Madden–Julian Oscillation (MJO), as a dominant mode of tropical intraseasonal oscillation, plays an important role in the variability of global weather and climate. However, current state‐of‐the‐art atmospheric circulation models have difficulty in reproducing observed MJO characteristics when forced by observed daily sea surface temperature alone. An important practical question is how much data a model needs in assimilation to reproduce real MJO events? By analysing ERA‐20C and NOAA‐20CR reanalysis data, the authors tried to figure out whether a model could reproduce observed MJO events by assimilating the observed surface signal alone. The phase propagation and vertical structure associated with MJO were compared between the reanalysis data and observations during 1979–2010. A total skill score considering both temporal correlation and spatial standard deviation were defined. The result showed that both ERA‐20C and NOAA‐20CR could reproduce the observed MJO characteristics very well, with the former superior to the latter, regardless of MJO intensity. Thus, a minimum requirement for an operational atmospheric model for MJO prediction is the assimilation of the observed surface signals.