Figures and text based on Zhang (2003) ; review of MJO in Journal of Geophysical Research. And George Kiladis (personal communication) MJO Lecture

Longitude-height schematic of MJO based on Madden and Julian (1972) Organised planetary scale system, influencing all of the tropics. Moves eastwards at about 5m/s Convective signal strongest in Indian Ocean and West/Central Pacific. Dynamic signal seen throughout the tropics. 1. Observations

MJO characterised by convectively active and inactive phases Phases connected by deep overturning zonal circulations Zonal winds reverse between lower and upper-levels 1. Observations

Zonal wind (2.5N-2.5S)Precipitation (1N-1S) (a)(b) Straight white lines: MJOs Black dashed lines: convectively coupled Kelvin waves White arrows indicate westward propagating Rossby or mixed Rossby-gravity waves 1. Observations MJO seen in unfiltered fields

1. Observations Positive period = eastward; Negative period = westward Note clear peaks of the MJO at days in ppn and zonal wind at 850hPa Wide range reflects highly episodic nature, and seasonal to interannual variability

1. Observations MJO phase speed of 5m/s distinguishes it from the fast convectively coupled Kelvin waves which propagate at greater speeds (15-17m/s). MJO moves faster when it does not have a convective signal (30-35m/s) Longitude Time (days) MJO composite based on regression of equatorial band-pass ( days) filtered 850 hPa zonal wind (contours, interval 0.2 m s -1 ) and precipitation (colors, mm day -1 ) upon 850 hPa zonal wind of the MJO at 160˚E and the equator. The MJO zonal wind was extracted from the band-pass filtered time series using its four leading modes of SVD (singular vector decomposition) (Zhang and Dong 2004). The straight cyan lines indicate the eastward phase speed of 5 m s -1.

1. Observations Large-scale wind structure is often described in terms of equatorial waves coupled to deep convection. Equatorial Kelvin wave to east, Equatorial Rossby wave to west: both considered essential to MJO.

1. Observations Immediately ahead of convective center are low-level convergence, ascending motions and low-level moistening; drying and low-levels to west. Encourages eastward propagation Diabatic heating

1. Observations Eastward moving convective center of active phase of MJO, made up of many higher frequency small scale convective systems moving in all directions Includes coupled Kelvin waves, and westward moving 2-day and 5- day disturbances (b) (c) (a) Longitude-time diagrams of deep cloud clusters (cloud top infrared temperature < 208 K) over 0˚ - 10˚S for (a) December 1992 during which an MJO event propagated through the eastern Indian and western Pacific Ocean (Yanai et al. 2000); (b) Details for December as marked by the lower right box in (a); (c) Details for December as marked by the box in (b). Sizes of ovals are proportional to the actual sizes of cloud clusters. (From Chen et al 1996)

1. Observations MJO signals in convection confined to Indian and Western Pacific Oceans Associated with warm SSTs known as the “warm pool” Note MJO signal in East Pacific north of cold tongue, in boreal summer; again emphasising the significance of warm SSTs. MJO undergoes string seasonal cycle; peaking in boreal winter/spring when strongest signals are immediately south of equator Variance of the MJO (contours) in (a) 850 hPa zonal wind and (b) precipitation during December – March, (c) 850 hPa zonal wind and (d) precipitation during June – September, overlaid with mean SST (˚C). Contour intervals are 1 m 2 s -2 for the wind starting from 2 m 2 s -2 and 2 mm 2 day -2 for precipitation starting from 2 mm 2 day -2. See Zhang and Dong (2004) for details of defining the MJO in this figure.

2. Mechanisms Since Kelvin wave is only eastward propagating equatoial wave and it resembles the MJO east of heating, the Kelvin wave has been “taken as the backbone of the MJO from day one” BUT, coupled Kelvin waves propagate eastwrds too fast Therefore key questions that must be addressed by any MJO theory are: What are the mechanisms that distinguish the MJO from convectively coupled Kelvin waves? What processes must take place to supply energy against dissipation to the MJO? Few theories answer these questions. There are two major schools of though on the energy source of the MJO: (I) Eastward propagation and coupling between convection and wind are secondary by-products of the atmospheric response to convection (II) The MJO creates its own energy source through atmospheric instability

2. Mechanisms (Atmospheric Response to Independent Forcing) (A)Intraseasonal variations in the Asian Monsoon have been proposed to be a forcing for MJO. Observations have suggested the existence of intraseasonal standing oscillations in convection, but these are NOT statistically significant. Idealised modelling studies also refute this hypothesis. (B)Tropical Stochastic Forcing: a localised stochastic heat source can give rise to oscillations at intraseasonal timescales. The maximum growth however is at smaller scales (zonal wave numbers > 4) (C)Lateral Forcing: Intraseasonal perturbations coherent with the MJO exist in the extratropics and may force MJOs. Eastward moving extratropical disturbances can excite a variety of equatorial waves.

2. Mechanisms (Atmospheric Instability) Instability theories tend to suffer the same problem in that the most unstable solutions tend to be at smallest scales “Special tricks” are required to remedy this; including +ve only heating and time-lags between the energy input and convective heating (A)Moisture Convergence These mechanisms are based on CISK (Conditional Instability of the Second Kind); where convective heating is related to low-level moisture convergence. For +ve only heating unstable modes move at 16-19m/s comparable to observed coupled Kelvin waves (not the MJO!). Growth rates are greatest on smallest scales. CISK often criticised as unphysical. Inclusion of Rossby wave slows moist Kelvin wave to more realistic values. (B) Surface Evaporation Wind-induced surface heat exchange (WISHE) has been proposed as a growth mechanism. Requires mean surface easterlies: then surface fluxes and convection peaks east of convective center (in warm phase of Kelvin wave, hence growth). BUT observations indicate that surface fluxes peak in or west of convective center. And mean low-levels winds rarely easterly in Indian Ocean and West Pacific!!!

CWC W Direction of Motion Temperature Structure of a Dry Kelvin Wave 2. Mechanisms (Atmospheric Instability)

Other Factors to consider: Radiation Water Vapor Sea Surface Temperature Scale Interaction Heating Profile

3. More Observations from Kiladis (2006) See Animation

The Madden-Julian Oscillation (MJO) Discovered by Rol Madden and Paul Julian at NCAR in 1971 Characterized by an envelope of convection ~10,000 km wide moving eastward at around 5 m/s Most active over regions of high sea surface temperature (> 27  C) Can have a profound impact on the extratropical circulation Is poorly represented in general circulation models, if at all Composed of a variety of higher frequency, smaller scale disturbances

from Wheeler and Kiladis, 1999 OLR power spectrum, 1979–2001 (Symmetric)

from Wheeler and Kiladis, 1999 OLR power spectrum, 1979–2001 (Symmetric) Kelvin Westward Inertio-Gravity Equatorial Rossby Madden-Julian Oscillation

OBSERVATIONS OF KELVIN WAVES AND THE MJO Time–longitude diagram of CLAUS T b (2.5S–7.5N), January–April 1987 Kelvin waves (15 m s -1 ) MJO (5 m s -1 )

3. More Observations from Kiladis (2006) OBSERVATIONS OF WAVES WITHIN THE MJO Time–longitude diagram of CLAUS T b (5S–equator), February 1987

OLR power spectrum, 1979–2001 (Symmetric) from Wheeler and Kiladis, 1999

Regression Models Simple Linear Model: y = ax + b where: x= predictor (filtered OLR) y= predictand (OLR, circulation)

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day 0 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day-16 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day-12 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day-8 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day-4 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day 0 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day+4 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day+8 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m 2 ) at eq, 155  E, Day+12 Streamfunction (contours 4 X 10 5 m 2 s -1 ) Wind (vectors, largest around 2 m s -1 ) OLR (shading starts at +/- 6 W s -2 ), negative blue

Specific Humidity at Truk (7.5  N,  E) Regressed against MJO- filtered OLR (scaled -40 W m 2 ) for OLR (top, Wm -2 ) Specific Humidity (contours, 1 X g kg -1 ), red positive OLR Pressure (hPa) from Kiladis et al. 2005

Q1 Regressed against MJO-filtered OLR over the IFA during COARE from Kiladis et al. 2005

Morphology of a Tropical Mesoscale Convective Complex in the eastern Atlantic during GATE (from Zipser et al. 1981) Storm Motion

Observed Kelvin wave morphology (from Straub and Kiladis 2003) Wave Motion

Two day (WIG) wave cloud morphology (from Takayabu et al. 1996)

Equatorial Wave Cloud Morphology Consistent with a progression of shallow to deep convection, followed by stratiform precipitation for the Kelvin, Westward Inertio-gravity (2-day) Waves, and Easterly Waves This was also observed during COARE for the MJO (e.g. Lin and Johnson 1996; Johnson et al. 1999; Lin et al. 2004) This evolution is similar to that occurring on the Mesoscale Convective Complex scale

Convection in General Circulation Models Question: How well do GCMs do in characterizing intraseasonal tropical convective variability? Jialin Lin et al. (2006) applied identical space-time spectral techniques to observed and modeled tropical precipitation Models used are the 14 coupled ocean-atmosphere GCMs used for intercomparison in the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC)

Rainfall Power Spectra, IPCC AR4 Intercomparison 15S-15N, (Symmetric) from Lin et al., 2006 Observations

Rainfall Power Spectra, IPCC AR4 Intercomparison 15S-15N, (Symmetric) from Lin et al., 2006

Rainfall Spectra/Backgr, IPCC AR4 Intercomparison 15S-15N, (Symmetric) from Lin et al., 2006 Observations

from Lin et al., 2006 Rainfall Spectra/Backgr, IPCC AR4 Intercomparison 15S-15N, (Symmetric)

Rainfall Spectra at 5S-5N, 85E from IPCC AR4 Intercomparison

4. Numerical Modeling (more comments from Zhang, 2005) Modeled eastward propagation speeds often closer to observed coupled convectively coupled Kelvin waves than MJO When eastward propagating signals are reproduced, they are too weak and structures unrealistic.

4. Numerical Modeling (more comments from Zhang, 2005) U at 850hPaPPN Obs All models (selected) produce some MJO signals Realistic spectra does not guarantee realistic structure (see next slide)

4. Numerical Modeling (more comments from Zhang, 2005) Common problem: +ve PPn anomalies tend to be in regions of low-level easterlies contrary to observations (in westerlies) Few models can reproduce observed MJO structures

5.Concluding Remarks Much progress has been made in past decade Still major challenges: need to better observe and understand vertical structure need to understand why some idealised models simulate MJOs better than more realistic GCMs Key research topics: scale interactions air-sea interaction prediction interaction with ENSO modulation of tropical cyclones interaction with monsoons influences on high latitude weather