Aerosol Effects upon Convective Cold Pools: Establishing General Trends
Active Dates | 9/1/2020-8/31/2024 |
---|---|
Program Area | Atmospheric System Research |
Project Description
Aerosol
Effects upon Convective Cold Pools: Establishing General Trends
Sonia Lasher-Trapp, University of Illinois (Principle Investigator)
A subset of soluble atmospheric aerosol particles called cloud condensation nuclei (CCN) are responsible
for the number of cloud droplets nucleated in Earth’s clouds, and a smaller subset of insoluble aerosol
particles nucleate ice in Earth’s clouds, called ice-nucleating particles (INP). These aerosol particles can
alter the microphysical processes by which a deep convective cloud produces precipitation. Other
environmental factors such as atmospheric stability, humidity and vertical wind shear are additional
controls on storm development and thus precipitation production. Of interest to the proposed work is the
potential importance of CCN and INP to the near-surface outflow from the convection, called cold pools,
that are driven by evaporating, melting, and sublimating hydrometeors within convective downdrafts.
Depending upon their intensity, depth, and propagation speed, cold pools can not only suppress future
cloud/storm development within their area of coverage by strongly stabilizing the lower atmosphere, but
also can incite new convective storms at their leading edges, potentially generating much more precipitation
for a given event. Numerous past numerical modeling studies have demonstrated a sensitivity of
precipitating convection and its cold pools to aerosol amounts, but this aspect has not been considered in
current efforts to parameterize cold pool effects for larger-scale weather and climate models. It is currently
unknown if these aerosol effects are of equal importance compared to larger-scale thermodynamic and
dynamic characteristics of the storm environment, as most studies have not considered how all of these
factors may change in tandem. The difficulty of collecting large, detailed data sets documenting potential
aerosol effects upon convective precipitation and the related cold pools, appropriate for hypothesis testing
and constraining and evaluating numerical model predictions, has hampered progress on this question.
The recent ARM-supported Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field deployment
in Argentina has collected a large data set with approximately 10 different cases in different environments
that can be used to study this question. Aircraft sampling with thermodynamic, dynamic, and microphysical
probes of developing convection on the days of interest provide information on the earliest development of
precipitation that may evolve into deep convection. When deep convection did occur, multiple ARM
scanning radars captured the evolution of the precipitation in vertical cross-sections, and sometimes the
subsequent development of cold pools. Several CACTI surface meteorological sites, as well as radiosonde
launches, also documented cold pool characteristics, and the environmental conditions in which they were
produced. Idealized numerical modeling will also be an important element in studying these cases, to test
the relative importance of the CCN, INP, and storm environment characteristics that may all contribute to
the cold pool characteristics, using our algorithms to quantify the latent cooling budgets of hydrometeors
in the downdrafts contributing to the cold pools.
This project will use a novel combination of analyses of CACTI data with numerical modeling
experimentation to improve our understanding and model representation of convective precipitation and
cold pool development. The outcomes of this project will include the production of case studies to test the
performance of existing and future cold pool parameterization schemes, and new knowledge regarding the
relative importance of aerosol to other environmental factors in determining cold pool characteristics. Such
knowledge is essential to understand and predict convective precipitation, and to determine the best ways
forward to expedite the development of more accurate parameterization schemes that represent cold pool
effects in large-scale models.
Sonia Lasher-Trapp, University of Illinois (Principle Investigator)
A subset of soluble atmospheric aerosol particles called cloud condensation nuclei (CCN) are responsible
for the number of cloud droplets nucleated in Earth’s clouds, and a smaller subset of insoluble aerosol
particles nucleate ice in Earth’s clouds, called ice-nucleating particles (INP). These aerosol particles can
alter the microphysical processes by which a deep convective cloud produces precipitation. Other
environmental factors such as atmospheric stability, humidity and vertical wind shear are additional
controls on storm development and thus precipitation production. Of interest to the proposed work is the
potential importance of CCN and INP to the near-surface outflow from the convection, called cold pools,
that are driven by evaporating, melting, and sublimating hydrometeors within convective downdrafts.
Depending upon their intensity, depth, and propagation speed, cold pools can not only suppress future
cloud/storm development within their area of coverage by strongly stabilizing the lower atmosphere, but
also can incite new convective storms at their leading edges, potentially generating much more precipitation
for a given event. Numerous past numerical modeling studies have demonstrated a sensitivity of
precipitating convection and its cold pools to aerosol amounts, but this aspect has not been considered in
current efforts to parameterize cold pool effects for larger-scale weather and climate models. It is currently
unknown if these aerosol effects are of equal importance compared to larger-scale thermodynamic and
dynamic characteristics of the storm environment, as most studies have not considered how all of these
factors may change in tandem. The difficulty of collecting large, detailed data sets documenting potential
aerosol effects upon convective precipitation and the related cold pools, appropriate for hypothesis testing
and constraining and evaluating numerical model predictions, has hampered progress on this question.
The recent ARM-supported Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field deployment
in Argentina has collected a large data set with approximately 10 different cases in different environments
that can be used to study this question. Aircraft sampling with thermodynamic, dynamic, and microphysical
probes of developing convection on the days of interest provide information on the earliest development of
precipitation that may evolve into deep convection. When deep convection did occur, multiple ARM
scanning radars captured the evolution of the precipitation in vertical cross-sections, and sometimes the
subsequent development of cold pools. Several CACTI surface meteorological sites, as well as radiosonde
launches, also documented cold pool characteristics, and the environmental conditions in which they were
produced. Idealized numerical modeling will also be an important element in studying these cases, to test
the relative importance of the CCN, INP, and storm environment characteristics that may all contribute to
the cold pool characteristics, using our algorithms to quantify the latent cooling budgets of hydrometeors
in the downdrafts contributing to the cold pools.
This project will use a novel combination of analyses of CACTI data with numerical modeling
experimentation to improve our understanding and model representation of convective precipitation and
cold pool development. The outcomes of this project will include the production of case studies to test the
performance of existing and future cold pool parameterization schemes, and new knowledge regarding the
relative importance of aerosol to other environmental factors in determining cold pool characteristics. Such
knowledge is essential to understand and predict convective precipitation, and to determine the best ways
forward to expedite the development of more accurate parameterization schemes that represent cold pool
effects in large-scale models.
Award Recipient(s)
- University of Illinois Urbana-Champaign (PI: Lasher-Trapp, Sonia)