Climate Dynamics

, Volume 51, Issue 1–2, pp 101–117 | Cite as

Regional and seasonal variations of the double-ITCZ bias in CMIP5 models

  • Ori Adam
  • Tapio Schneider
  • Florent Brient


Current climate models represent the zonal- and annual-mean intertropical convergence zone (ITCZ) position in a biased way, with an unrealistic double precipitation peak straddling the equator in the ensemble mean over the models. This bias is seasonally and regionally localized. It results primarily from two regions: the eastern Pacific and Atlantic (EPA), where the ITCZ in boreal winter and spring is displaced farther south than is observed; and the western Pacific (WP), where a more pronounced and wider than observed double ITCZ straddles the equator year-round. Additionally, the precipitation associated with the ascending branches of the zonal overturning circulations (e.g., Walker circulation) in the Pacific and Atlantic sectors is shifted westward. We interpret these biases in light of recent theories that relate the ITCZ position to the atmospheric energy budget. WP biases are associated with the well known Pacific cold tongue bias, which, in turn, is linked to atmospheric net energy input biases near the equator. In contrast, EPA biases are shown to be associated with a positive bias in the cross-equatorial divergent atmospheric energy transport during boreal winter and spring, with two potential sources: tropical biases associated with equatorial sea surface temperatures (SSTs) and tropical low clouds, and extratropical biases associated with Southern Ocean clouds and north Atlantic SST. The distinct seasonal and regional characteristics of WP and EPA biases and the differences in their associated energy budget biases suggest that the biases in the two sectors involve different mechanisms and potentially different sources.


ITCZ Double-ITCZ bias Atmospheric energy budget CMIP5 models 

List of symbols

\(\langle \cdot \rangle\)

Mass-weighted column integration

\((\cdot )^\dagger\)

Divergent flux component

\((\cdot )_0\)

Equatorial average (5\(^\circ\)S–5\(^\circ\)N)

\((\cdot )_{\phi _1-\phi _2}\)

Area-weighted meridional average between latitudes \(\phi _1\) and \(\phi _2\)


Moist enthalpy


Moist static energy


Tropical precipitation asymmetry index


Equatorial precipitation index


Atmospheric energy transport

\(\langle vh \rangle _0^\dagger\), \({\text{AET}}_0^\dagger\)

Meridional component of the cross-equatorial divergent atmospheric energy flux

\(\langle uh \rangle _0^\dagger\)

Equatorial average of the zonal component of the divergent atmospheric energy flux


Energy flux equator


Energy flux prime meridian


Atmospheric net energy input


Local atmospheric net energy input (NEI plus zonal energy fluxes across atmospheric columns) minus energy storage


Double-ITCZ bias


ECMWF interim reanalysis


Eastern Pacific and Atlantic sector (240\(^\circ\)E–0\(^\circ\))


Western Pacific sector (150\(^\circ\)E–240\(^\circ\)E)



We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (Fig. 1) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We would also like to thank our anonymous reviewers for their contributions to the presentation of this work.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Hebrew University of JerusalemJerusalemIsrael
  2. 2.ETH ZürichZürichSwitzerland
  3. 3.California Institute of TechnologyPasadenaUSA
  4. 4.Centre National de Recherches MétéorologiquesMétéo-France/CNRSToulouseFrance

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