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## Detection of Equatorial Waves in Data

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### Conclusion 2: A portion of tropical convective activity is organized by equatorially trapped waves of Matsuno’s shallow water theory

### Conclusion 2: A portion of tropical convective activity is organized by equatorially trapped waves of Matsuno’s shallow water theory

### Conclusion 2: A portion of tropical convective activity is organized by equatorially trapped waves of Matsuno’s shallow water theory

Conclusion 1: Large scale atmospheric waves modulate waves and convection (along with the diurnal cycle) on smaller scales

### Conclusion 2: A portion of tropical convective activity is organized by equatorially trapped waves of Matsuno’s shallow water theory

Conclusion 1: Large scale atmospheric waves modulate waves and convection (along with the diurnal cycle) on smaller scales

### Conclusion 2: A portion of tropical convective activity is organized by equatorially trapped waves of Matsuno’s shallow water theory

Conclusion 3: Equatorial waves have a warm lower troposphere ahead of the wave, with cooling behind. The mid-troposphere is warm within the convective region

### Summary and Question

### Summary and Question

### Convection in General Circulation Models

Temperature at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

### Outstanding Issues

Space-Time Spectrum of JJA Symmetric OLR, 15S-15N

Kelvin

“TD” band

MJO

Eq. Rossby

Wheeler and Kiladis, 1999

Space-Time Spectrum of JJA Antisymmetric OLR, 15S-15N

Inertio-

Gravity

“TD” band

MJO

Wheeler and Kiladis, 1999

Space-Time Spectrum of JJA Antisymmetric OLR, 15S-15N

Wheeler and Kiladis, 1999

Temperature at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

OLR (top, Wm-2)

Temperature (contours, .1 °C), red positive

from Straub and Kiladis 2002

Temperature at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

Wave Motion

OLR (top, Wm-2)

Temperature (contours, .1 °C), red positive

from Straub and Kiladis 2002

where

is the vertical wavenumber

is the equivalent depth

is the vertical wavelength

is the scale height

Using Representative Numbers for the Tropical Stratosphere:

“Peak Projection

Response”

for h=200 m, c=45 m/s, Lz=12.0 km

Using Representative Numbers for the Tropical Stratosphere:

“Peak Projection

Response”

for h=200 m, c=45 m/s, Lz=12.0 km

Convectively coupled Kelvin

for h=30 m, c=15 m/s, Lz=4.0 km

Using Representative Numbers for the Tropical Stratosphere:

“Peak Projection

Response”

for h=200 m, c=45 m/s, Lz=12.0 km

Convectively coupled Kelvin

for h=30 m, c=15 m/s, Lz=4.0 km

for c=5 m/s, Lz=1.2 km

MJO

Zonal Wind at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

OLR (top, Wm-2)

Zonal Wind (contours, .25 ms-1), red positive

from Straub and Kiladis 2002

Temperature at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

Wave Motion

OLR (top, Wm-2)

Temperature (contours, .1 °C), red positive

from Straub and Kiladis 2002

Specific Humidity at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

Wave Motion

OLR (top, Wm-2)

Specific Humidity (contours, 1 X 10-1 g kg-1), red positive

from Straub and Kiladis 2002

TOGA COARE Temperature (2S, 155E) Regressed against Westward Inertio Gravity-filtered OLR (scaled -40 W m2)

Wave Motion

Temperature (contours, .1 °C), red positive

Haertel and Kiladis 2004

TOGA COARE Specific Humidity (2S, 155E) Regressed against Westward Inertio Gravity-filtered OLR (scaled -40 W m2)

Wave Motion

Specific Humidity (contours, 1 X 10-1 g kg-1), red +

Haertel and Kiladis 2004

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day 0

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

from Kiladis et al. 2005

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day-16

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day-12

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day-8

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day-4

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day 0

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day+4

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day+8

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

OLR and 850 hPa Flow Regressed against MJO-filtered OLR (scaled -40 W m2) at eq, 155E, 1979-1993

Day+12

Streamfunction (contours 4 X 105 m2 s-1)

Wind (vectors, largest around 2 ms-1)

OLR (shading starts at +/- 6 W s-2), negative blue

Zonal Wind at Honiara (10S, 160E) Regressed against MJO-filtered OLR (scaled -40 W m2) for 1979-1999

OLR

Pressure

(hPa)

Wave Motion

OLR (top, Wm-2)

U Wind (contours, .5 ms-1), red positive

from Kiladis et al. 2005

Temperature at Honiara (10S, 160.0E) Regressed against MJO-filtered OLR (scaled -40 W m2) for 1979-1999

OLR

Pressure

(hPa)

Wave Motion

OLR (top, Wm-2)

Temperature (contours, .1 °C), red positive

from Kiladis et al. 2005

Specific Humidity at Truk (7.5N, 152.5E) Regressed against MJO-filtered OLR (scaled -40 W m2) for 1979-1999

OLR

Pressure

(hPa)

Wave Motion

OLR (top, Wm-2)

Specific Humidity (contours, 1 X 10-1 g kg-1), red positive

from Kiladis et al. 2005

Lag-height regressions of OSA specific humidity vs. moisture budget-derived rainrate. The data are progressively regridded to coarser time intervals ((a) 6 h, (b) 1 day, and (c) 4 days), and a light high-pass filter is used for each panel (cutoff period six times the lag window width). (d) The original unfiltered 6 h data are used, with a very wide lag window. Contour unit is 0.1 g/kg per mm/h.

from Mapes et al. 2006

Conclusion 1: Large scale atmospheric waves modulate waves and convection (along with the diurnal cycle) on smaller scales

Conclusion 1: Large scale atmospheric waves modulate waves and convection (along with the diurnal cycle) on smaller scales

Conclusion 3: Equatorial waves have a warm lower troposphere ahead of the wave, with cooling behind. The mid-troposphere is warm within the convective region

Conclusion 1: Large scale atmospheric waves modulate waves and convection (along with the diurnal cycle) on smaller scales

Conclusion 3: Equatorial waves have a warm lower troposphere ahead of the wave, with cooling behind. The mid-troposphere is warm within the convective region

Conclusion 4: Low level moisture is high ahead of the waves (high CAPE) and is lofted rapidly into the mid-troposphere as deep convection develops, with drying occurring at low levels first while it is still moist aloft behind the waves

TOGA COARE Diabatic Heating Q1 (2S, 155E) Regressed against Westward Inertio Gravity-filtered OLR (scaled -40 W m2)

Wave Motion

Wave Motion

Diabatic Heating (contours, °K/day), red +

Haertel and Kiladis 2004

Radar Derived Divergence and Omega Regressed against Rain Rate

Regression composite of the MCS life cycle in divergence and vertical motion. Plotted are averages of regression

sections from seven tropical radar deployments (see Mapes and Lin, 2005 for details). (a) VAD divergence regressed against rainrate for a circular area of 96 km diameter, contour unit 10−6 s−1 per mm/h. (b) The corresponding mass flux (pressure units, but with positive sign indicating upward motion), contour unit 10 h Pa/day per mm/h.

from Mapes et al. 2006

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)

Wave Motion

from Benedict and Randall, 2007

Generalized Evolution of a Convectively Coupled Equatorial Wave

from Kiladis et al., 2009

Conclusion 3: Equatorial waves have a warm lower troposphere ahead of the wave, with cooling behind. The mid-troposphere is warm within the convective region

Conclusion 4: Low level moisture is high ahead of the waves (high CAPE) and is lofted rapidly into the mid-troposphere as deep convection develops, with drying occurring at low levels first while it is still moist aloft behind the waves

Conclusion 4: Low level moisture is high ahead of the waves (high CAPE) and is lofted rapidly into the mid-troposphere as deep convection develops, with drying occurring at low levels first while it is still moist aloft behind the waves

Conclusion 5: Equatorial wave cloud morphology is consistent with a progression from shallow to deep convection, followed by stratiform rain during the passage of the wave

All waves examined have broadly self-similar vertical structures in terms of their dynamical fields (temperature, wind, pressure, diabatic heating, cloud morphology)

This is consistent with a progression of shallow to deep convection, followed by stratiform precipitation from the mesoscale on up to the MJO

Suggests a fundamental interaction between wave dynamics and convection across a wide range of scales

All waves examined have broadly self-similar vertical structures in terms of their dynamical fields (temperature, wind, pressure, diabatic heating, cloud morphology)

This is consistent with a progression of shallow to congestus and then deep convection, followed by stratiform precipitation from the mesoscale on up to the MJO

Suggests a fundamental interaction between wave dynamics and convection across a wide range of scales

Is a systematic cascade of energy from the mesoscale on up to the planetary scale crucial for the maintenance of equatorial waves?

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)

Observations

from Lin et al., 2006

Rainfall Power Spectra, IPCC AR4 Intercomparison 15S-15N, (Symmetric)

from Lin et al., 2006

Rainfall Spectra/Backgr, IPCC AR4 Intercomparison 15S-15N, (Symmetric)

Observations

from Lin et al., 2006

Rainfall Spectra/Backgr, IPCC AR4 Intercomparison 15S-15N, (Symmetric)

from Lin et al., 2006

Rainfall Spectra/Backgr., IPCC AR4 Intercomparison 15S-15N, (Antisymm.)

Observations

from Lin et al., 2006

Rainfall Spectra/Backgr., IPCC AR4 Intercomparison 15S-15N, (Antisymm.)

from Lin et al., 2006

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

Observed KWs: Upper troposphere

OLR (shading); ECMWF 200-hPa u, v (vectors), streamfunction (contours)

- Divergence collocated with/to the west of lowest OLR
- Zonal winds near equator
- Rotational circulations off of equator

MPI

MRI

Precipitation (shading); 200-hPa u, v (vectors); streamfunction (contours)

Model KWs: Upper troposphere

Wave Motion

OLR (top, Wm-2)

Temperature (contours, .1 °C), red positive

from Straub and Kiladis 2002

Specific Humidity at Majuro (7N, 171E) Regressed against Kelvin-filtered OLR (scaled -40 W m2) for 1979-1999

Wave Motion

OLR (top, Wm-2)

Specific Humidity (contours, 1 X 10-1 g kg-1), red positive

from Straub and Kiladis 2002

General Circulation Models do a relatively poor job in correctly simulating variability in tropical convection (but not necessarily its mean state)

Is this due to the misrepresentation of convection itself, or its coupling to the large scale (or both)?

Is convection even parameterizable in models?

Improvements in the representation of tropical convection will lead to improvements in medium-range weather forecasts in mid-latitudes (and perhaps to ENSO)

What is the impact of poor tropical variability in GCMs on climate change scenarios?

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