Spatial and Temporal Variability of Vertical Velocity under Shallow Cumulus

Abstract Vertical velocity distribution below cloud is one of the key determinants of cloud life cycle, but observations of this variable are extremely sparse in space. Doppler lidar retrievals and large-eddy simulations at the U.S. Department of Energy’s Atmospheric Radiation Measurement User Facility Southern Great Plains site are used to determine whether vertical velocity statistics from temporally dense profiles at a single location can be substituted for spatial vertical velocity statistics. We show that even a small number (five) of widely distributed [ O (1°) latitude/longitude spacing] lidars is sufficient sampling to reconstruct domainwide spatial vertical velocity variance, but not higher moments of the vertical velocity distribution. Spatial and temporal vertical velocity variances in the Doppler lidar observations are nearly interchangeable as long as the spatial variance is temporally averaged and the temporal variance is averaged across lidars. This is true even though the dominant spatial scales of vertical velocity variability are , more than an order of magnitude smaller than the spacing between the lidars. In the limit where the temporal variance does not vary across a spatial domain (e.g., if the meteorological and surface forcing of the atmospheric turbulence is homogeneous across the domain) and the domain-mean vertical velocity is zero, the commonly available retrieval of temporal vertical velocity variance at one site is equivalent to the spatial variance over the domain. We use an updraft parcel model to show that substituting temporal for spatial vertical velocity statistics will have a relatively minor effect on cloud droplet number concentrations.

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Publication Details

Journal
Monthly Weather Review
Published
2025-04-18
DOI
https://doi.org/10.1175/mwr-d-24-0055.1
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
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article

Spatial and Temporal Variability of Vertical Velocity under Shallow Cumulus

Colleen Kaul, Gavin C. Cornwell, Kôichi Sakaguchi, William I. Gustafson et al.
Monthly Weather Review
Atmospheric aerosols and clouds
article

Spatial and Temporal Variability of Vertical Velocity under Shallow Cumulus

Colleen Kaul, Gavin C. Cornwell, Kôichi Sakaguchi, William I. Gustafson, Heng Xiao, Jerome D. Fast, Rob Newsom, Vincent E. Larson, Larry K. Berg, Brian Gaudet, Johannes Mülmenstädt, Duli Chand
article en

Abstract

Abstract Vertical velocity distribution below cloud is one of the key determinants of cloud life cycle, but observations of this variable are extremely sparse in space. Doppler lidar retrievals and large-eddy simulations at the U.S. Department of Energy’s Atmospheric Radiation Measurement User Facility Southern Great Plains site are used to determine whether vertical velocity statistics from temporally dense profiles at a single location can be substituted for spatial vertical velocity statistics. We show that even a small number (five) of widely distributed [ O (1°) latitude/longitude spacing] lidars is sufficient sampling to reconstruct domainwide spatial vertical velocity variance, but not higher moments of the vertical velocity distribution. Spatial and temporal vertical velocity variances in the Doppler lidar observations are nearly interchangeable as long as the spatial variance is temporally averaged and the temporal variance is averaged across lidars. This is true even though the dominant spatial scales of vertical velocity variability are , more than an order of magnitude smaller than the spacing between the lidars. In the limit where the temporal variance does not vary across a spatial domain (e.g., if the meteorological and surface forcing of the atmospheric turbulence is homogeneous across the domain) and the domain-mean vertical velocity is zero, the commonly available retrieval of temporal vertical velocity variance at one site is equivalent to the spatial variance over the domain. We use an updraft parcel model to show that substituting temporal for spatial vertical velocity statistics will have a relatively minor effect on cloud droplet number concentrations.

Monthly Weather ReviewVol. 153(5)
Pacific Northwest National Laboratory (US), University of Wisconsin–Milwaukee (US)
Openalex Percentile: Top 91%
Atmospheric aerosols and clouds
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