Composite Regression Analysis of the Eight Phases of the MJO
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Transcript Composite Regression Analysis of the Eight Phases of the MJO
Composite Regression Analysis of
the 8 Phases of the MJO
By: Zachary Handlos
Introduction
MJO – What is it?
8 phases of MJO
Convective phases vs. suppressed phases
MJ 1971 – origins of oscillation
MJ 1994 – Brief History of Research (ie:
observational work, Super Clusters, Monsoons, etc...)
Wheeler and Hendon (2004)
Performed EOF analysis of combined fields (OLR,
zonal wind at 850 hPa and 200 hPa)
Subtracted out as much seasonal, annual variability
as possible (ie: ENSO, etc...)
RMM1 and RMM2 = EOF1 and EOF2
Explain MJO propagation over space
RMM1 – enhanced convection over Maritime Continent
RMM 2 – enhanced convection over the Pacific
Goal of This Project:
Understand WH (2004) statistical methods by
recreating some of their work
Show the significance of the RMM1 and RMM2
EOF's and their relationship to the MJO, forecasting
the MJO
For this presentation, results regarding the
composite regression analysis of OLR data
considered
Composite Regression Analysis
ESRL (NCEP) interpolated OLR data (2.5 deg
resolution, daily for May-June)
Subtracted out mean
Regressed OLR onto RMM 1 and RMM2
Call the regression vectors r1 and r2
Composite Regression Analysis
Calculate the value of the OLR regression slope
values as a combination of RMM1, RMM2:
r = r1-i*r2
OLR = Re{r*exp(i*[(9*π/8)+(j*(π/4))])]} where
j = phase (1-8)
i = sqrt(-1)
Wait Zak...what are you doing here?
Wheeler and Hendon (2004) phase space diagram
Represent MJO phases with combined RMM value
Multiply r by the second term on the RHS of
previous equation to composite regression into the 8
phases
Want the real part of equation
My Results vs. Wheeler and Hendon
(2004)
Used complex, combined RMM regression vector
and composite based on earlier algorithm
WH (2004) composite OLR (and wind) anomalies
based on results from phase space diagram (Fig. 7
in paper)
Time Frame analyzed:
1990-2004 (Me)
1974-2003 (WH 2004)
Future Work (Current Research)
Focus: ISCCP cloud regimes (Rossow et al, 2005)
Currently looking at the shape of latent heating
profiles, calculating shapes using only precipitation
and surface convergence in the ITCZ
Idea: Look at evolution of latent heating profiles,
clouds within MJO phases (and SCC's)
Statistical Analysis methods such as composite
analysis, EOF analysis, even spectral analysis could
be useful
References
Madden, R. A. and P. R. Julian, 1971: Detection of a 40-50-day oscillation in the zonal wind in the tropical
Pacific. J. Atmos. Sci., 28:702–708.
Madden, R. A. and P. R. Julian, 1972: Description of global scale circulation cells in the Tropics with a 4050-day period. J. Atmos. Sci., 29:1109–1123.
Madden, R. A. and P. R. Julian, 1994: Observations of the 40–50-day tropical oscillation—A review. Mon.
Wea. Rev., 122:814–837.
Tromeur, E., and W.B. Rossow, 2010: Interaction of tropical deep convection with the large-scale circulation
in the MJO. J. Climate, 23, 1837-1853, doi:10.1175/202009JCLI3240.1
Wheeler, Matthew C., Harry 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.