The Iris Hypothesis Revisited:

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The Iris Hypothesis Revisited Analysis of Upper
Tropospheric Cloud Variations with SST using
Aura MLS and Aqua AIRS Observations Hui
Su Jonathan H. Jiang, Daniel Feldman (Caltech),
Yu Gu (UCLA) Acknowledgements William G.
Read, Dong L. Wu, Michael J. Schwartz Joe W.
Waters, Nathaniel J. Livesey, Michelle L.
Santee Microwave Atmospheric Science Team Jet
Propulsion Laboratory California Institute of
Technology
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Introduction

• Cloud feedback is one of greatest uncertainties
  in climate modeling and climate prediction
• Upper tropospheric (UT) clouds reduce outgoing
  longwave radiation (OLR) to space, causing a
  warming effect they also increase planetary
  albedo and reduce incoming solar radiation,
  producing a cooling effect
• Upper tropospheric clouds are closely related to
  UT humidity and its greenhouse effect (e.g. Su et
  al. 2006).
• It is important to quantify the net radiative
  effects of UT clouds and their changes with
  surface temperature, and the associated feedbacks

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Existing Studies on Clouds and SST Relation
Tropical deep convection increases with SST
(Ramanathan and Collins 1991 Waliser et al.
1993 Collins et al. 1996 Lin et al. 1995 Lau
et al. 1997 Bony et al. 1997 Tompkins and Craig
1999) Do UT clouds increase or decrease with SST?
(Lindzen et al. 2001 Hartmann and Michelsen
2002 Lin et al. 2001, 2004 Del Genio et al.
2002)
Do Clouds have positive or negative climate
feedback?
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Spatial Variation of UT Clouds with SST
Su et al. (2006) showed that UT cloud ice
increases with SST when SST is greater than 300
K, leading to a moistened UT and enhanced water
vapor greenhouse effect.
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The Iris Hypothesis (Lindzen et al. 2001, BAMS)
Cloud Fraction
Cloud Fraction
Scatterplots showing how cirrus coverage varies
with cloud-weighted SST (From Fig. 5 in Lindzen
et al., BAMS, 2001). They argued that cirrus
cloud coverage normalized by a measure of cumulus
coverage decreases about 22 per degree increase
of SST, implying a negative climate feedback that
would more than cancel all the positive feedbacks
in current climate models.
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Highlights of Lindzen et al. (2001) Analysis

• Simplify global circulation using a 3.5-box
  model

Cloudy /moist
Clear/ moist
Clear/Dry
Tropics
Extra-tropics

• Used daily mean cloud fraction and
  cloud-weighted SST relation over W. Pacific to
  infer clouds-SST relation for climate change
• Radiative transfer calculations were based on
  assumed optical properties of clouds to match
  radiation budget from ERBE

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Iris Seen in AIRS Cloud Fraction-SST Relation
Over the western Pacific convective region
(130?E-170?W, 30?S-30?N), area-averaged AIRS
cirrus cloud fraction decreases 6 (20 relative
change) with 1 K increase of SST.
Scatter plots of area-averaged daily Aqua-AIRS
cirrus cloud fraction (with cloud top pressure
less than 400 hPa) over the region 130?E-170?W,
30?S-30?N for the period of August 04 to November
05 versus Aqua-MODIS simultaneous SST.
However, cloud fraction represents only one
aspect of cloud properties. Without cloud optical
thickness information, it is not possible to
compute the radiative effect of clouds. The MLS
IWC measurement provides the 3-D information of
cloud mass. Thus it is a better measure to
account for cloud radiative effects.
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Revisit the Iris Hypothesis

• Using Aura MLS cloud ice water content
  (IWC) measurements, and Aqua MODIS SST and CERES
  radiative fluxes data to tackle the clouds-SST
  relationship
• Advantages of MLS cloud IWC data
• Cloud mass measurement in the UT
• Cloud vertical profiles
• Simultaneous measurements of UT H2O and
  Temperature
• Approach
• Simplify tropical circulation using a two-box
  model cloudy and clear boxes
• Note the box boundaries are time-dependent,
  based on IWC gt 0 mg/m3
• Examine how the mean IWC over the cloudy area
  changes with SST
• Examine how UT H2O and T changes with SST
• Compute the changes of top-of-atmosphere (TOA)
  and surface radiative fluxes associated with the
  changes of clouds, UT H2O and T using the Fu-Liou
  radiation model
• Quantify the climate feedback parameters for each
  variable

where G is net TOA fluxes, and A can be IWC, T
and H2O
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Using Daily MODIS SST Data
NCEP SST weekly or monthly Aqua MODIS SST
daily, nearly simultaneous with Aura MLS IWC
measurements
Shown on the left is the annual-mean IWC vs. NCEP
and MODIS SSTs for all tropical oceanic boxes
within 30S-30N (spatial variability). In
following discussions, we will examine the mean
IWC changes averaged over the cloudy areas in
relation to daily MODIS SST changes (temporal
variability).
Compared to NCEP SST, the MODIS SST has
approximately 2 K cold bias across the entire
tropics. Other SST data (e.g. NCEP, TMI) will be
used later.
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Use a time-dependent cloudy area
100 hPa
147 hPa
215 hPa
Cloudy area fraction
Cloudy area fraction
Cloudy area fraction
y 0.54 x 152.63 R 0.3
y 0.23 x 66.71 R 0.3
y 0.023 x 6.69 R 0.2
IWC
IWC
IWC
The mean IWC over the tropical cloudy area
(30S-30N) increases about 10 per degree K
increase of SST, while the fraction of
cloudy-area is insensitive to SST changes.
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Simultaneous UT H2O and T changes
y 7.7 x 1836.2 R 0.08
y 1.2 x 120.5 R 0.4
H2O
Temperature
y 5.9 x 1650.5 R 0.3
y 1.0 x 85.3 R 0.5
H2O
Temperature
y 0.88 x 247.8 R 0.2
y 0.62 x 10.4 R 0.4
H2O
Temperature
The 316-147 hPa water vapor increases by 6 per
degree increase of SST.
The 316-147 hPa temperature increases by 1 K per
degree increase of SST.
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MLS-observed UT Cloud Forcing
Define cloud forcing as
IR?TOA SW?TOA IR?SFC SW?SFC
30S-30N (W/m2) ?25.6 (Warming) 6.8 (Cooling) 1.3 (Warming) ?8.5 (Cooling)
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Radiative Impact of UT Cloud Change
When UT (215 hPa and up) IWC increases 10 for 1
K increase of SST, the changes of TOA fluxes are
about 2 to 4 W m?2, dominated by warming effect
due to reduced OLR. UT clouds have a positive
feedback to global warming
IR?TOA SW?TOA IR?SFC SW?SFC
30S-30N (W m?2 K?1) ?1.3 (Warming) 0.4 (Cooling) 0.1 (Warming) ?0.5 (Cooling)
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Coupled UT H2O, Clouds and T Changes
The increase of UT H2O at 6 per degree increase
of SST would produce a positive feedback of 0.1
W m?2 K?1. The increase of UT temperature at 1 K
per degree increase of SST would provide a
negative feedback, about 0.5 W m?2 K?1.
Verification of these results using other
datasets and model simulations are needed!
IR?TOA SW?TOA IR?SFC SW?SFC
30S-30N (W m?2 K?1) ?0.9 (Warming) 0.4 (Cooling) 0.1 (Warming) ?0.5 (Cooling)
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Summary

• The UT clouds-SST relationship depends on spatial
  and temporal scales in question.
• Tropical daily cloudy-area averaged mean IWC
  increases approximately 10 per degree of SST
  increase, accompanied by 6 increase of UT water
  vapor and about 1 K increase of UT temperature.
• The MLS-observed UT clouds have a net warming
  effect to the climate system. Thus the increase
  of UT clouds with SST would produce a positive
  feedback to global warming.
• The increase of UT water vapor enhances positive
  feedback by clouds, while the increase of UT
  temperature tends to mitigate the positive cloud
  feedback.
• Our preliminary analysis using MLS IWC
  measurements shows disagreement with Lindzen et
  al. (2001) Iris hypothesis in terms of
  cloud-climate feedback.