Atmospheric Feedbacks Over the Pacific Cold-tongue: Results From Models and

Observations

De-Zheng Sun and Tao Zhang

CIRES/Climate Diagnostics Center

& ESRL/Physical Science Division

http://www.cdc.noaa.gov/~ds

In collaboration with

Curt Covey and Steve Klein

Lawrence Livermore National Laboratory

Bill Collins, Jim Hack, Jeff Kiehl, and Jerry Meehl

National Center for Atmospheric Research

Isaac Held

Geophysical Fluid Dynamics Laboratory

Max Suarez

National Aronics and Space Administration

Why feedbacks?

• Feedbacks determine the sensitivity of the climate system to an external perturbation

• Feedbacks determine the amplitude of the natural variability in the climate system

• Feedbacks determine the equilibrium state of the climate system--the time-mean climate

Why feedbacks over the Pacific cold-tongue?

• The cold-tongue plays a key role in the heat and carbon balance of the climate system and is a major source region of climate variability

• Climate models do not simulate the cold-tongue properly: they have a tendency to develop an excessive cold-tongue.

The Excessive Cold-tongue in coupled models Annual Mean SST from observations and CGCMs

Ideas about the causes of the excessive cold-tongue

• Insufficient resolution of the ocean model (Stockdale et al. 1998, Kessler et al. 1998)

• Lack of phytoplankton in the ocean model (Murtugudde et al. 2002)

• A weaker regulating effect from the model atmosphere (Sun et al. 2003)

The idea of a weaker regulating effect from the

model atmosphere?

Could it be that the strength of one or more negative feedbacks in the model underestimated? Or alternatively, could it be that the strength of the one or more positive feedbacks in the model is over estimated?

The effect of a less negative net atmospheric feedback on the cold-tongue SST bias

€

T −T0 =H(T0)

4σT03 − (

∂Ga∂T

+∂Cl∂T

+∂Cs∂T

+∂Da∂T

) −∂Do∂T

Atmospheric Feedbacks

€

∂Do∂T

= −13wm−2K−1

€

(∂Ga∂T

+∂Cl∂T

+∂Cs∂T

+∂Da∂T

)

M

SST Bias

Net flux error at T0

Ocean feedback

A further assessment of the effect of feedback errors on the cold-tongue

SST

Perturbed run with feedbacks from CAM1

Perturbed run with observed feedbacks

Control run

Coupled model used: NCAR Pacific basin model coupled with an empirical atmosphere (Sun 2003)

Methodology

• Use ENSO as the forcing signal and obtain the feedbacks by examining the response of various energy fluxes to SST changes associated with El Nino and La Nina

Data

•Observational data: ERBE, NCEP/NCAR reanalysis, ISCCP

•Model outputs: AMIP runs of climate models

The Physical Processes

The Water Vapor Feedback

The Dynamical Feedback

The Cloud Feedbacks

ERBE

CAM1CAM1

The Cloud Feedbacks

The Cloud Feedbacks

Response of Cs to El Nino warming

(W/m

2/K)

Response of Precipitation to El Nino Warming

Response of Cloud Cover in CAM1 CAM1

Atmospheric feedbacks in observations and the NCAR models

How are other models doing in simulating the feedbacks?

Precipitation Response to El Nino Warming

Summary and Conclusion• These results confirm the suspicion that

an underestimate of the regulating effect from the equatorial atmosphere is a prevalent problem in climate models.

• Most models underestimate the strength

of the negative feedbacks of cloud albedo and atmospheric transport. All models overestimate of the positive feedback from water vapor.

• The results highlight the need to validate the feedback from the ocean transport.

Water vapor response

Oceanic Issues

• What’s the effect of ENSO on the time-mean upper ocean temperature?

Atmospheric Issues

• What are the processes that control the equatorial precipitation?

• How is the vertical distribution of clouds determined?

• Why does convection in the models have a stronger moistening effect on the upper troposphere?

El Nino in climate models

La Nina in Climate Models

The Asymmetry between El Nino and La

Nina

Sk.=0.62

Sk.=0.30

Sk.=0.05

Sk.=-0.10

Sk.=-0.20

Sk.=0.29