Climate and Dynamics
A comparison of the interannual variability in atmospheric angular momentum and length-of-day using multiple reanalysis data sets
Article first published online: 16 OCT 2012
©2012. American Geophysical Union. All Rights Reserved.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 117, Issue D20, 27 October 2012
How to Cite
2012), A comparison of the interannual variability in atmospheric angular momentum and length-of-day using multiple reanalysis data sets, J. Geophys. Res., 117, D20102, doi:10.1029/2012JD018105., and (
- Issue published online: 16 OCT 2012
- Article first published online: 16 OCT 2012
- Manuscript Accepted: 8 SEP 2012
- Manuscript Revised: 6 SEP 2012
- Manuscript Received: 14 MAY 2012
- angular momentum;
- length of day;
 This study performs an intercomparison of the interannual variability of atmospheric angular momentum (AAM) in eight reanalysis data sets for the post-1979 era. The AAM data are further cross validated with the independent observation of length-of-day (LOD). The intercomparison reveals a close agreement among almost all reanalysis data sets, except that the AAM computed from the 20th Century Reanalysis (20CR) has a noticeably lower correlation with LOD and with the AAM from other data sets. This reduced correlation is related to the absence of coherent low-frequency variability, notably the Quasi-biennial Oscillation, in the stratospheric zonal wind in 20CR. If the upper-level zonal wind in 20CR is replaced by its counterpart from a different reanalysis data set, a higher value of the correlation is restored. The correlation between the AAM and the Nino3.4 index of tropical Pacific SST is also computed for the reanalysis data sets. In this case, a close agreement is found among all, including 20CR, data sets. This indicates that the upward influence of SST on the tropospheric circulation is well captured by the data assimilation system of 20CR, which only explicitly incorporated the surface observations. This study demonstrates the overall close agreement in the interannual variability of AAM among the reanalysis data sets. This finding also reinforces the view expressed in a recent work by the authors that the most significant discrepancies among the reanalysis data sets are in the long term mean and long-term trend.