Boundary Layer and Orographic Controls on Convection Initiation during CACTI
Active Dates | 8/15/2021-8/14/2024 |
---|---|
Program Area | Atmospheric System Research |
Project Description
Boundary layer and orographic controls on
convection
initiation during CACTI
Dr. Neil Lareau, University of Nevada, Reno (Principal Investigator)
Dr. Daniel Kirshbaum, McGill University (Co-Investigator)
Data from ARM's Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted over the Sierras de Córdoba mountain range of Argentina provide a unique opportunity to advance our understanding of orographic moist convection (i.e., storms and clouds forming over mountains). These CACTI data are scientifically valuable not only for probing the growth of deep convection in this region, but also for studying the links between orographic and boundary-layer forcing mechanisms and convective outcomes (e.g., shallow versus deep cumuli). To this end, this proposal aims to gain insight into how variations in these forcings modulate the vigor, depth, and extent of convective clouds over the Sierras de Córdoba using a combination of observations and simulations. This will be accomplished by answering the following questions:
1. How do variations in thermal and mechanical forcing for ascent over the Sierras de Córdoba modulate convective outcomes during CACTI?
2. How predictable is regime-dependent orographic convection in modern atmospheric prediction models?
The analyses used to answer these questions will include (a) classifying orographic forcing regimes and their convective outcomes from radar, satellite, radiosonde, and surface observations, (b) quantifying the impact of regime dependent sub-cloud and in-cloud processes on convective outcomes using boundary layer observations and cloud-layer entrainment retrievals, and (c) quantifying convective-scale predictability of CACTI events using ensembles numerical prediction experiments.
In completing these tasks we will advance the understanding of orographic moist convection and, more broadly, contribute to ASR’s goals of understanding how cloud processes affect the Earth’s radiative balance and hydrological cycle, including processes that limit the predictive skill of regional and global models.
Dr. Neil Lareau, University of Nevada, Reno (Principal Investigator)
Dr. Daniel Kirshbaum, McGill University (Co-Investigator)
Data from ARM's Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted over the Sierras de Córdoba mountain range of Argentina provide a unique opportunity to advance our understanding of orographic moist convection (i.e., storms and clouds forming over mountains). These CACTI data are scientifically valuable not only for probing the growth of deep convection in this region, but also for studying the links between orographic and boundary-layer forcing mechanisms and convective outcomes (e.g., shallow versus deep cumuli). To this end, this proposal aims to gain insight into how variations in these forcings modulate the vigor, depth, and extent of convective clouds over the Sierras de Córdoba using a combination of observations and simulations. This will be accomplished by answering the following questions:
1. How do variations in thermal and mechanical forcing for ascent over the Sierras de Córdoba modulate convective outcomes during CACTI?
2. How predictable is regime-dependent orographic convection in modern atmospheric prediction models?
The analyses used to answer these questions will include (a) classifying orographic forcing regimes and their convective outcomes from radar, satellite, radiosonde, and surface observations, (b) quantifying the impact of regime dependent sub-cloud and in-cloud processes on convective outcomes using boundary layer observations and cloud-layer entrainment retrievals, and (c) quantifying convective-scale predictability of CACTI events using ensembles numerical prediction experiments.
In completing these tasks we will advance the understanding of orographic moist convection and, more broadly, contribute to ASR’s goals of understanding how cloud processes affect the Earth’s radiative balance and hydrological cycle, including processes that limit the predictive skill of regional and global models.
Award Recipient(s)
- University of Nevada Reno (PI: Lareau, Neil)