Could MJO Predictions help for forecasting the Australian
monsoon?
Motivation
The MJO is typically at its strongest and most coherent during the southern
hemisphere summer. During this season, the MJO displays greatest variability
of low-level winds and convection across the eastern Indian Ocean and
western Pacific between the equator and about 15°S (e.g., Fig.1).
This region encompasses the Australian and related Indonesian summer
monsoons. Thus great potential for MJO-induced variability of these monsoon
systems exists.
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Figure1. Composite OLR and 850-hPa
wind anomalies for eight phases of the MJO during December/January/February
(DJF). The phases are defined according to the analysis of Wheeler
and Hendon (2004), with each phase lasting for an average of 6
days during an MJO cycle. OLR contour interval is 7.5 W m-2, with
the colour scale as shown. Black vectors indicate wind anomalies
that are statistically significant at the 90% level, with the magnitude
of the largest vector shown on the bottom-right of each panel. |
Research Summary
The climatological peak of the Australian monsoon occurs in January and
February, while monsoon onset typically occurs around mid to late December.
Considerable intraseasonal variability of the monsoon rainfall and circulation
occurs with each monsoon season being composed of a number of “bursts” and “breaks”,
each lasting from a few days to a week or more. A greater portion of
this variability can be ascribed to the MJO than to any other intraseasonal
mode. During years of strong MJO variability, a large-scale envelope
of convection sweeps eastward across the region every 30-90 days, together
with changes in low-level winds from easterly to westerly (Fig.1). The
precipitation variation associated with a typical MJO event has amplitude
of up to 6 mm/day in the far northern coastal region (Fig.2, Phases 5
and 6 versus Phase 2), which is comparable to the standard deviation
of weekly rainfall.
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Figure 2. As in Fig.1, except for
composites of
rainfall and wind over Australia. The precipitation
contour interval is 1 mm/day, with additional contours drawn at
+-0.5 mm/day. Only those rainfall anomalies that are statistically
significant at the 90% level are shaded. Sourced from http://www.bom.gov.au/bmrc/clfor/cfstaff/
matw/maproom/RMM/index.htm. |
The MJO modulates the large-scale conditions associated with onset of
the Australian monsoon, but it does not set the exact date of onset.
For instance, at Darwin (12.5°S, 130.9°E) onset rarely occurs
during the convectively suppressed phases of the MJO (Phases 8, 1, 2,
and 3; Fig. 3), while onset tends to occur in a wide range of the convectively
active phases of the MJO (Phases 4, 5, 6, and 7). Thus, while the MJO
appears to act as a modulator of the large-scale conditions associated
with onset of the monsoon, onset in a particular year is set by a smaller
scale event such as a tropical cyclone or passage of a midlatitude synoptic-scale
trough embedded in the larger-scale envelope.
Figure 3. Darwin onset dates (as
defined by Drosdowsky, 1996) in the MJO phase space of Wheeler
and Hendon (2004). The numbers 1 through 8 (large and black) have
the same meaning as the Phases of Figs. 1 and 2. RMM1 and RMM2
are the projection coefficients of the leading pair of empirical
orthogonal functions of near-equatorial convection and winds, as
are used to define the MJO phases. A blue number is plotted for
each monsoon onset, being the year of the nearest December. For
example, at the onset of the 1996/97 monsoon, the MJO was in Phase
6 (near the top of figure). |
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Implications
The robust impact of the MJO on the Australian monsoon,
together with demonstrated predictability of the MJO at lead times approaching
~3 weeks, implies the possibility of useful monsoon predictions (e.g.,
onset date or periods of above normal and below normal rainfall accumulation)
at these lead times.
Future Work In the short-term, extended range prediction of the large-scale dynamical
fields associated with the MJO needs to be translated into predictions
of parameters of direct relevance to agriculture and hydrology. In the
long-term, improvements in the representation of the MJO in dynamical
forecast models should allow for prediction of the full range of MJO-related
monsoon variability.
Further Reading Drosdowsky, W., 1996: Variability of the Australian summer monsoon at
Darwin: 1957-1992. J. Climate, 9, 85-96.
Hendon, H.H. and B. Liebmann, 1990b: The intraseasonal (30-50 day) oscillation
of the Australian summer monsoon. J. Atmos. Sci., 47, 2909-2923.
Wheeler, M.C. and H.H. Hendon, 2004: An all-season real-time multivariate
MJO index: Development of an index for monitoring and prediction. Mon.
Wea. Rev., 132, 1917-1932.
Wheeler, M.C. and J.L. McBride, 2005: Australian-Indonesian monsoon. In:
W.K.M. Lau and D.E. Waliser (eds), Intraseasonal Variability in the
Atmosphere-Ocean Climate System. Praxis, Springer Berlin Heidelberg,
pages 125-173.
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