Publication Abstracts

Naud et al. 2019, in press

Naud, C.M, J.F. Booth, J. Jeyaratnam, L.J. Donner, C.J. Seman, M. Zhao, H. Guo, and Y. Ming, 2019: Extratropical cyclone clouds in the GFDL climate model: Diagnosing biases and the associated causes. J. Climate, in press, doi:10.1175/JCLI-D-19-0421.1.

The clouds in southern hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of AM4, a model GFDL will utilize for CMIP6, the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low-levels (again by differing amounts), especially in the post-cold frontal (PCF) region, when compared to observations. Focusing on only the models, their differences in high and mid-level clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

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BibTeX Citation

@unpublished{na03400r,
  author={Naud, C. M and Booth, J. F. and Jeyaratnam, J. and Donner, L. J. and Seman, C. J. and Zhao, M. and Guo, H. and Ming, Y.},
  title={Extratropical cyclone clouds in the GFDL climate model: Diagnosing biases and the associated causes},
  year={2019},
  journal={J. Climate},
  doi={10.1175/JCLI-D-19-0421.1},
  note={Manuscript accepted for publication}
}

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RIS Citation

TY  - INPR
ID  - na03400r
AU  - Naud, C. M
AU  - Booth, J. F.
AU  - Jeyaratnam, J.
AU  - Donner, L. J.
AU  - Seman, C. J.
AU  - Zhao, M.
AU  - Guo, H.
AU  - Ming, Y.
PY  - 2019
TI  - Extratropical cyclone clouds in the GFDL climate model: Diagnosing biases and the associated causes
JA  - J. Climate
DO  - 10.1175/JCLI-D-19-0421.1
ER  -

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