Public Abstract

DE-SC0025466: Linking convective environments to microphysical processes in updrafts and downdrafts using DOE ARM data and high-resolution modeling

Award Status: Active

Institution: Board of Regents of the University of Oklahoma, Norman, OK
UEI: EVTSTTLCEWS5
DUNS: 848348348

Most Recent Award Date: 08/26/2024
Number of Support Periods: 1
PM: Nasiri, Shaima

Current Budget Period: 09/01/2024 - 02/28/2026
Current Project Period: 09/01/2024 - 08/31/2027
PI: Lebo, Zachary

Supplement Budget Period: N/A

Public Abstract

Linking convective environments to microphysical processes in updrafts and downdrafts using DOE ARM data and high-resolution modeling Zachary J. Lebo, University of Oklahoma (Principal Investigator) Thunderstorms form when air in clouds rises spontaneously, extending to great heights in the Earth’s atmosphere. The rapidly rising air is fundamentally a result of air in the thunderstorm cloud being less dense that its surroundings, causing it to be buoyant and thus rise, akin to a beach ball at the bottom of a swimming pool rising rapidly to the water’s surface when released. These thunderstorm clouds, or deep convective clouds, involve characteristics and processes that span a wide range of scales, from 10s-1000s of kilometers (i.e., temperature, humidity, winds, etc.) to 10s-1000s of micrometers (i.e., the size of individual cloud drops, rain drops, ice crystals, snow, graupel, and hail, hereafter referred to collectively as ‘hydrometeors’). The environment in which deep convective clouds form helps determine the dynamics of these clouds, as well as the various processes ongoing in their updrafts at the scale of individual hydrometeors. Ultimately, these processes influence the production of precipitation and downdrafts associated with thunderstorms, which can have important feedbacks on the evolution and strength of thunderstorms. Understanding this linkage between the characteristics of the environment, the dynamics of deep convective clouds, the ongoing processes at the scale of individual hydrometeors, and the feedbacks on the characteristics and evolution of these clouds is a primary goal of the Tracking Aerosol Convection Interactions Experiment (TRACER) and is essential for the accurate prediction of these clouds in both weather forecast and climate models. Accurate parameterization, simulation, and forecasting of deep convective clouds requires a fundamental scientific understanding of the aforementioned linkages between 1) the characteristics of the environments in which deep convective clouds form, 2) the convective cloud properties, 3) the processes and properties of individual hydrometeors, 4) the downstream impacts on precipitation and downdrafts, and 5) feedbacks on the evolution of the convective updrafts. While prior studies have provided important results regarding individual or a few of these items, many questions remain regarding the full linkage across all aspects and scales, in particular the link between hydrometeor properties/processes and their feedbacks on the characteristics and evolution of deep convective clouds. Therefore, in this project, we aim to address the following core science questions: 1. How do the characteristics of deep convective cloud updrafts and downdrafts relate to the properties of the environments in which they form? 2. How do hydrometeor properties and processes in deep convective cloud updrafts impact downdraft properties, and how are they related to environmental factors? 3. How do hydrometeor processes and properties in deep convective cloud updrafts and downdrafts affect the evolution of these clouds? These questions will be addressed by analyzing the extensive database of observations collected from the recent TRACER field campaign (including radar wind profiler, radar, and radiosonde observations), supplemented with high-resolution real-case simulations of deep convective clouds targeted by the radar observations. Processes affecting the evolution of hydrometeors in the observed deep convective clouds will be identified through a novel “fingerprinting” approach applied to the radar data. To relate parameters of the environment in which the observed deep convective clouds formed to the convective cloud properties/processes as well as the hydrometeor properties/processes, multivariate statistical analyses will be performed. Furthermore, to account for large-scale weather patterns influencing the deep convective clouds, clustering algorithms will be used to categorize these patterns. Lastly, high-resolution numerical simulations using the Weather Research and Forecasting Model will enable us to extend the correlations gleaned from the TRACER data analysis to causation, relying on sensitivity simulations performed with perturbed cloud and precipitation processes. The use of real-case simulations is aimed at providing a robust and broadly applicable relation between hydrometeor processes and deep convective cloud evolution. The results of this project will improve the fundamental understanding of deep convective clouds and hydrometeor properties, with broader implications for improved cumulus parameterization and severe weather forecasting.

Linking convective environments to microphysical processes in updrafts and downdrafts using DOE ARM data and high-resolution modeling
Zachary J. Lebo, University of Oklahoma (Principal Investigator)

Thunderstorms form when air in clouds rises spontaneously, extending to great heights in the Earth’s atmosphere. The rapidly rising air is fundamentally a result of air in the thunderstorm cloud being less dense that its surroundings, causing it to be buoyant and thus rise, akin to a beach ball at the bottom of a swimming pool rising rapidly to the water’s surface when released. These thunderstorm clouds, or deep convective clouds, involve characteristics and processes that span a wide range of scales, from 10s-1000s of kilometers (i.e., temperature, humidity, winds, etc.) to 10s-1000s of micrometers (i.e., the size of individual cloud drops, rain drops, ice crystals, snow, graupel, and hail, hereafter referred to collectively as ‘hydrometeors’). The environment in which deep convective clouds form helps determine the dynamics of these clouds, as well as the various processes ongoing in their updrafts at the scale of individual hydrometeors. Ultimately, these processes influence the production of precipitation and downdrafts associated with thunderstorms, which can have important feedbacks on the evolution and strength of thunderstorms. Understanding this linkage between the characteristics of the environment, the dynamics of deep convective clouds, the ongoing processes at the scale of individual hydrometeors, and the feedbacks on the characteristics and evolution of these clouds is a primary goal of the Tracking Aerosol Convection Interactions Experiment (TRACER) and is essential for the accurate prediction of these clouds in both weather forecast and climate models.

Accurate parameterization, simulation, and forecasting of deep convective clouds requires a fundamental scientific understanding of the aforementioned linkages between 1) the characteristics of the environments in which deep convective clouds form, 2) the convective cloud properties, 3) the processes and properties of individual hydrometeors, 4) the downstream impacts on precipitation and downdrafts, and 5) feedbacks on the evolution of the convective updrafts. While prior studies have provided important results regarding individual or a few of these items, many questions remain regarding the full linkage across all aspects and scales, in particular the link between hydrometeor properties/processes and their feedbacks on the characteristics and evolution of deep convective clouds. Therefore, in this project, we aim to address the following core science questions:

1. How do the characteristics of deep convective cloud updrafts and downdrafts relate to the properties of the environments in which they form?

2. How do hydrometeor properties and processes in deep convective cloud updrafts impact downdraft properties, and how are they related to environmental factors?

3. How do hydrometeor processes and properties in deep convective cloud updrafts and downdrafts affect the evolution of these clouds?

These questions will be addressed by analyzing the extensive database of observations collected from the recent TRACER field campaign (including radar wind profiler, radar, and radiosonde observations), supplemented with high-resolution real-case simulations of deep convective clouds targeted by the radar observations. Processes affecting the evolution of hydrometeors in the observed deep convective clouds will be identified through a novel “fingerprinting” approach applied to the radar data. To relate parameters of the environment in which the observed deep convective clouds formed to the convective cloud properties/processes as well as the hydrometeor properties/processes, multivariate statistical analyses will be performed. Furthermore, to account for large-scale weather patterns influencing the deep convective clouds, clustering algorithms will be used to categorize these patterns. Lastly, high-resolution numerical simulations using the Weather Research and Forecasting Model will enable us to extend the correlations gleaned from the TRACER data analysis to causation, relying on sensitivity simulations performed with perturbed cloud and precipitation processes. The use of real-case simulations is aimed at providing a robust and broadly applicable relation between hydrometeor processes and deep convective cloud evolution. The results of this project will improve the fundamental understanding of deep convective clouds and hydrometeor properties, with broader implications for improved cumulus parameterization and severe weather forecasting.