### Abstract

Using high resolution simulations of eight well-documented cloud cases in different climate regimes, this study investigated the statistical distributions of dynamic and thermodynamic variables in the cloud layer and examined various assumptions used by the current statistical cloud schemes. It is found that dynamic and thermodynamic variables skew differently in the cloud layer of shallow cumulus, stratocumulus, and deep convective clouds. Vertical velocity is positively skewed, but the skewed dynamic structure cannot account for the large skewness of positively skewed total mixing ratio q
_{t} and negatively skewed liquid water potential temperature θ
_{l}. It is, thus, not physically sound to assume that the sub-grid variation of different variables follows the same skewed PDF. The simulations further show that the weighted standard deviations of q
_{t} and θ
_{l} have the same order of magnitude in all types of clouds, indicating that the variations of temperature and moisture are the equally important factors for sub-grid clouds. Thus, neglecting either one of them in a statistical cloud scheme may introduce significant bias in the parameterized clouds.

Original language | English (US) |
---|---|

Article number | L05807 |

Journal | Geophysical Research Letters |

Volume | 36 |

Issue number | 5 |

DOIs | |

State | Published - Mar 16 2009 |

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### ASJC Scopus subject areas

- Earth and Planetary Sciences(all)
- Geophysics

### Cite this

*Geophysical Research Letters*,

*36*(5), [L05807]. https://doi.org/10.1029/2008GL036817

**On the use of PDF schemes to parameterize sub-grid clouds.** / Zhu, Ping; Zuidema, Paquita.

Research output: Contribution to journal › Article

*Geophysical Research Letters*, vol. 36, no. 5, L05807. https://doi.org/10.1029/2008GL036817

}

TY - JOUR

T1 - On the use of PDF schemes to parameterize sub-grid clouds

AU - Zhu, Ping

AU - Zuidema, Paquita

PY - 2009/3/16

Y1 - 2009/3/16

N2 - Using high resolution simulations of eight well-documented cloud cases in different climate regimes, this study investigated the statistical distributions of dynamic and thermodynamic variables in the cloud layer and examined various assumptions used by the current statistical cloud schemes. It is found that dynamic and thermodynamic variables skew differently in the cloud layer of shallow cumulus, stratocumulus, and deep convective clouds. Vertical velocity is positively skewed, but the skewed dynamic structure cannot account for the large skewness of positively skewed total mixing ratio q t and negatively skewed liquid water potential temperature θ l. It is, thus, not physically sound to assume that the sub-grid variation of different variables follows the same skewed PDF. The simulations further show that the weighted standard deviations of q t and θ l have the same order of magnitude in all types of clouds, indicating that the variations of temperature and moisture are the equally important factors for sub-grid clouds. Thus, neglecting either one of them in a statistical cloud scheme may introduce significant bias in the parameterized clouds.

AB - Using high resolution simulations of eight well-documented cloud cases in different climate regimes, this study investigated the statistical distributions of dynamic and thermodynamic variables in the cloud layer and examined various assumptions used by the current statistical cloud schemes. It is found that dynamic and thermodynamic variables skew differently in the cloud layer of shallow cumulus, stratocumulus, and deep convective clouds. Vertical velocity is positively skewed, but the skewed dynamic structure cannot account for the large skewness of positively skewed total mixing ratio q t and negatively skewed liquid water potential temperature θ l. It is, thus, not physically sound to assume that the sub-grid variation of different variables follows the same skewed PDF. The simulations further show that the weighted standard deviations of q t and θ l have the same order of magnitude in all types of clouds, indicating that the variations of temperature and moisture are the equally important factors for sub-grid clouds. Thus, neglecting either one of them in a statistical cloud scheme may introduce significant bias in the parameterized clouds.

UR - http://www.scopus.com/inward/record.url?scp=65649146447&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=65649146447&partnerID=8YFLogxK

U2 - 10.1029/2008GL036817

DO - 10.1029/2008GL036817

M3 - Article

AN - SCOPUS:65649146447

VL - 36

JO - Geophysical Research Letters

JF - Geophysical Research Letters

SN - 0094-8276

IS - 5

M1 - L05807

ER -