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Detection of Equatorial Waves in Data. OLR power spectrum, 1979–2001 (Symmetric). from Wheeler and Kiladis, 1999. Space-Time Spectrum of JJA Symmetric OLR, 15  S-15  N. Kelvin. “TD” band. MJO. Eq. Rossby. Wheeler and Kiladis, 1999.

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slide2

OLR power spectrum, 1979–2001 (Symmetric)

from

Wheeler and Kiladis, 1999

slide4

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

Kelvin

“TD” band

MJO

Eq. Rossby

Wheeler and Kiladis, 1999

slide5

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

Inertio-

Gravity

“TD” band

MJO

Wheeler and Kiladis, 1999

slide26

Temperature at Majuro (7N, 171E) 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

slide27

Temperature at Majuro (7N, 171E) 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

slide28

Linear Theory Predicts:

where

is the vertical wavenumber

is the equivalent depth

is the vertical wavelength

is the scale height

slide29

Using Representative Numbers for the Tropical Stratosphere:

“Peak Projection

Response”

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

slide30

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

slide31

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

slide32

Zonal Wind at Majuro (7N, 171E) 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

slide33

Temperature at Majuro (7N, 171E) 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

slide34

Specific Humidity at Majuro (7N, 171E) 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

slide35

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

Wave Motion

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

Haertel and Kiladis 2004

slide36

TOGA COARE Specific Humidity (2S, 155E) 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

slide37

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

slide38

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

slide39

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

slide40

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

slide41

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

slide42

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

slide43

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

slide44

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

slide45

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

slide46

Zonal Wind at Honiara (10S, 160E) 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

slide47

Temperature at Honiara (10S, 160.0E) 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

slide48

Specific Humidity at Truk (7.5N, 152.5E) 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

slide49

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

slide50

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

slide51

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

slide52

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

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

slide53

TOGA COARE Diabatic Heating Q1 (2S, 155E) 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

slide54

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

slide56
Morphology of a Tropical Mesoscale Convective Complex in the eastern Atlantic during GATE (from Zipser et al. 1981)

Storm Motion

slide59

MJO Propagation

from Benedict and Randall, 2007

slide61

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

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

slide62

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

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

summary and question

Summary and Question

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

summary and question1

Summary and Question

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?

convection in general circulation models

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)

slide66

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

Observations

from Lin et al., 2006

slide68

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

Observations

from Lin et al., 2006

slide70

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

Observations

from Lin et al., 2006

models with good kw variability

CCSR, Japan

GISS-AOM, USA

GISS-ER, USA

GISS-EH, USA

Models with good KW variability
observed kws upper troposphere
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
slide75

MIUB

MPI

MRI

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

Model KWs: Upper troposphere

slide76

Temperature at Majuro (7N, 171E) 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

slide78

Specific Humidity at Majuro (7N, 171E) 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

outstanding issues

Outstanding Issues

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?