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Understanding Convective Cloud Evolution through Analysis of ARM AMF3 Surface, Radar, GOES-16 Satellite Observations, and Numerical Model Simulations

Active Dates 9/1/2023-8/31/2026
Program Area Atmospheric System Research
Project Description
Understanding Convective Cloud Evolution through Analysis of ARM AMF3 Surface, Radar, GOES-16 Satellite Observations, and Numerical Model Simulations

Principal Investigator

John R. Mecikalski, University of Alabama in Huntsville


Jason A. Otkin, University of Wisconsin–Madison, Space Science and Engineering Center

David S. Henderson, University of Wisconsin–Madison, Space Science and Engineering Center


Major unknowns remain in understanding of cloud processes leading to the growth of cumulus clouds, specifically cumulus cloud updraft behaviors before and during convective initiation (CI), which is generally defined as the time when a cloud develops into a mature cumulonimbus cloud. Convective clouds are often challenging to simulate accurately in numerical weather prediction (NWP) models because of complex interactions between radiation, surface energy and moisture fluxes, and the growth of the planetary boundary layer. Ground-based ARM AMF3 observations are critical for observing the details of convective cloud updrafts, cloud base information, and planetary boundary layer conditions maintaining the clouds, whereas high-resolution and frequent (1-5 minute) geostationary satellite observations are key to observing the evolution of cloud top characteristics. The proposed research will focus on cumulus clouds that evolve into other cumulus cloud types, and that may undergo CI, and how the land surface and lower-tropospheric conditions impact these processes.

Key science questions the project seeks to answer are: (1) How do ARM-observed cumulus cloud features, dynamics, and surface fluxes relate to satellite-observed cloud-top characteristics, how these relationships vary during transitions between cumulus cloud types, and how these are associated with CI success or failure, and (2) How does spatial heterogeneity at the land surface influence cloud growth surrounding the AMF3 station, and how can that information be used to guide ARM development efforts in Alabama? In order to answer these questions, the research focus will be on days characterized by humid boundary layers dominated by cumulus clouds either with or without developing convective storms during the 2023-2025 warm seasons. The focus will be on conducting pilot studies using AMF3 surface and planetary boundary layer observations and satellite cloud property retrievals to provide new insight into the evolution of cumulus clouds before, during, and after CI, as a function of planetary boundary layer structure and land surface conditions. The project’s main goal is to increase understanding on how ground-based observations can augment information provided by geostationary satellites, which together can be used to inform and improve the accuracy of NWP models. The ARM AMF3 datasets will be collected along with simultaneous 1-5 min resolution cumulus cloud datasets from the Advanced Baseline Imager on GOES-16.

The project has the following expected outcomes: Seek to uncover and discern macrophysical cumulus cloud properties from combined ground- and satellite- observations, and how the science community can gain more information on convective clouds and CI from satellite-based fields compared to what is presently known; examine how conditions in the lower troposphere affect transitions in cloud type, cloud growth rates, and the longevity of cumulus clouds leading either to CI success or failure; and, assess sensitivities of the land surface model and planetary boundary layer parameterization schemes to the observed cloud fields for CI and non-CI events.
Award Recipient(s)
  • University of Alabama in Huntsville (PI: Mecikalski, John)