Chunqiang Wu, Tianjun Zhou, Dezheng Sun

Email: wucq@mail.iap.ac.cn

An extended analysis of atmospheric responses over the tropical Pacific: results from atmospheric GCMs

LASG, Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing

UAW, Tokyo, Jul. 2, 2008

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Contents

Background and Data1

Thermodynamic response2

Conclusions3

Net surface heat flux,

Clear sky green house effect,

Cloud radiative forcings,

Latent heat flux,

etc.

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Background (I)

Stephen 2005 J. Clim.

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Method 1: Checked the differences in the feedbacks of water

vapor and clouds in global warming among different models.

(Wetherald and Manabe,1989; Cess et al. 1990, 1996)

Background (II)

Two Methods:

model inter-comparison Individual feedbackBut, without OBS validation

Method 2: Compared the response of water vapor and clouds to

SST changes over the time scales for which observational data

are available. (Sun and Held 1996, Soden 1997, Held and Soden 2000)

Recent result: Current AGCMs tend to overestimate the water

vapor feedback and underestimate the cloud albedo

feedback. (Sun et al., 2006)

1)What are the responses in a longer time period and in more models?

2)What are these biases related to?

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Data:

Observation: ISCCP FD, OAFLux,NCEP1

Model: AMIP type model results (16 models, for clarity , only 7 typical

models are presented).

Period: 1985 to 1998

Method:

Regress the corresponding components to SST anomaly

over the cold tongue region (5oS-5oN, 150oE-110oW).

Data

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Contents

Background and Data1

Thermodynamic response2

Conclusions3

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Ga clear sky greenhouse effect

LWCRF longwave cloud radiative forcing

SWCRF shortwave cloud radiative forcing

Da atmospheric energy transport

Da is defined as the difference of net longwave/shortwave radiation, latent/sensible heat flux at the surface and at the top of

the atmosphere. Fs net surface heat flux

Fs ~ Ga+LWCRF+SWCRF+Da+black body emission

Variables in this section

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Overview of responses

1) All models, except MPI ECHAM5, underestimate the response of net surface heat flux to El Nino warming.

2) All models overestimate the response of clear sky green house effect to El Nino warming.

3) Response of short wave radiative forcing gives rise to the largest uncertainty among models. But not all models under estimate this response.

4) The uncertainty from the response of atmospheric energy transport is also very large, which, mainly, is from the response of latent heat flux.

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Net surface heat flux

Net surface heat flux damps the change of SST over the equatorial Pacific during ENSO

MPI model reasonably reproduces the response of net surface heat flux

Others have weak responses, most of them have positive responses over the central equatorial Pacific

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Clear sky greenhouse effect

The response of clear sky greenhouse effect is similar to the ENSO pattern. It relates to the change of water vapor and temperature profile to El Nino warming.

Models simulate a similar pattern to the observation, but with a much large magnitude, especially over the central equatorial Pacific.

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Water vapor and temperature profile

The percentage response of water vapor at the middle level troposphere contributes to the bias in clear sky greenhouse effect.

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Shortwave radiative forcing

In observation, the negative response of short wave radiative forcing located in the central equatorial region. Over other regions, there are slight positive responses.

Models tend to under estimate the negative response over the central equatorial Pacific. Also, there is some unrealistic positive response over the eastern equatorial Pacific.

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Latent heat flux (hfls)

In observation, latent heat flux decreases over the eastern central equatorial Pacific during El Nino warming, while the response over the western equatorial Pacific is weak. Models can capture the negative response over the eastern part well, but the response in the western part is positive.

Positive for downward

Latent heat flux ~ specific humidity difference

and surface wind speed

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Specific humidity difference (Qs-Qair)

Models show similar response pattern to the observation.

Except MRI model, others under estimate the response.

Qs: surface saturation

specific humidity

Qair: surface air specific

humidity

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Surface wind speed (10m)

Surface wind speed response is over estimated over the central equatorial Pacific, which is corresponding to the bias of latent heat flux

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Contents

Background and Data1

Thermodynamic response2

Conclusions3

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Conclusions

All models overestimates the response of clear sky greenhouse effect to El Nino warming, which is related to the excessive response of water vapor in the middle level troposphere .

Most models show deficient shortwave response, which is related to the response of convection.

All models have excessive positive latent heat flux (downward) response in the central tropical Pacific, which is caused by excessive surface wind speed response to El Nino warming.

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