Incorporating ARM TRACER Campaign Data into a Fine-Resolution WRF-Chem-SBM Data Assimilation Framework: Sensitivity ANalysis of Microphysics and Thermodynamics to CCN Profile
Active Dates | 8/1/2022-7/31/2025 |
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Program Area | Atmospheric System Research |
Project Description
The role of clouds in regulating surface precipitation and the atmosphere's radiation balance makes it an essential component of the global climate system. The formation of cloud particles results from the condensation of water vapor on the surface of
aerosol
particles, which act as
cloud condensation nuclei
or ice nuclei. Significant progress has indeed been made in recent decades; however, the fundamental physical mechanisms of
aerosol-cloud interactions
are still poorly understood, and there is a need to reduce their uncertainties in climate forcing.
While measurements of clouds' microphysical/thermodynamic characteristics and aerosol concentrations could provide crucial information that enhances our understanding of the aerosol-cloud interaction within the atmosphere, explaining its chemical and physical processes is not possible without model integration. Conventional modeling setups lack incorporating aerosol-cloud interaction-relevant observations, and designing a common data assimilation framework would necessarily add stiffness to the aerosol-cloud interaction-related equations. To address this issue, we propose developing and implementing a novel data assimilation framework for studying aerosol-cloud interaction without considering the overriding effects of either aerosols or clouds. Using data from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) TRacking Aerosol Convection Interaction ExpeRiment (TRACER) campaign, we will determine accurate initial and boundary conditions for a target convective cell for data assimilation and fine-resolution modeling. We will use the Weather Research and Forecasting model coupled with the chemistry and spectral bin model, which explicitly calculates the cloud-relevant microphysical processes/interactions and treats aerosol-cloud interactions through aerosol activation and resuspension.
With this novel data assimilation framework, we will address the following research questions:
1. What is the role of various aerosol particles in forming cloud condensation nuclei? How does a cloud condensation nuclei profile in a convective cell perturb the atmospheric microphysics and thermodynamics associated with clouds, including but not limited to the size distribution of cloud droplets, the ice water path, and liquid water path, the distribution of latent heat, the intensity (mixed-phase invigoration) and frequency of updraft/downdrafts, the horizontal advection resulting from entrainment/detrainment, and the overall impact on total precipitation?
2. How do various aerosols act as cloud condensation nuclei in intensifying convective strength over the boundary layer and in the lower free troposphere?
3. What is the effect of clouds’ microphysical properties on the formation of secondary organic/inorganic aerosols, influencing the evolution of particle size distribution and eventually altering the vertical profile of cloud condensation nuclei?
4. How do aerosol particles influence the radiative forcing of clouds, such as changes in the albedo, formation frequency, and lifetime of clouds?
Upon completing this project, we will deliver a modeling framework that uses the data from the Atmospheric Radiation Measurements to accurately and comprehensively explain the interaction between clouds and aerosols and thus reduce the current uncertainties in climate forcing.
While measurements of clouds' microphysical/thermodynamic characteristics and aerosol concentrations could provide crucial information that enhances our understanding of the aerosol-cloud interaction within the atmosphere, explaining its chemical and physical processes is not possible without model integration. Conventional modeling setups lack incorporating aerosol-cloud interaction-relevant observations, and designing a common data assimilation framework would necessarily add stiffness to the aerosol-cloud interaction-related equations. To address this issue, we propose developing and implementing a novel data assimilation framework for studying aerosol-cloud interaction without considering the overriding effects of either aerosols or clouds. Using data from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) TRacking Aerosol Convection Interaction ExpeRiment (TRACER) campaign, we will determine accurate initial and boundary conditions for a target convective cell for data assimilation and fine-resolution modeling. We will use the Weather Research and Forecasting model coupled with the chemistry and spectral bin model, which explicitly calculates the cloud-relevant microphysical processes/interactions and treats aerosol-cloud interactions through aerosol activation and resuspension.
With this novel data assimilation framework, we will address the following research questions:
1. What is the role of various aerosol particles in forming cloud condensation nuclei? How does a cloud condensation nuclei profile in a convective cell perturb the atmospheric microphysics and thermodynamics associated with clouds, including but not limited to the size distribution of cloud droplets, the ice water path, and liquid water path, the distribution of latent heat, the intensity (mixed-phase invigoration) and frequency of updraft/downdrafts, the horizontal advection resulting from entrainment/detrainment, and the overall impact on total precipitation?
2. How do various aerosols act as cloud condensation nuclei in intensifying convective strength over the boundary layer and in the lower free troposphere?
3. What is the effect of clouds’ microphysical properties on the formation of secondary organic/inorganic aerosols, influencing the evolution of particle size distribution and eventually altering the vertical profile of cloud condensation nuclei?
4. How do aerosol particles influence the radiative forcing of clouds, such as changes in the albedo, formation frequency, and lifetime of clouds?
Upon completing this project, we will deliver a modeling framework that uses the data from the Atmospheric Radiation Measurements to accurately and comprehensively explain the interaction between clouds and aerosols and thus reduce the current uncertainties in climate forcing.
Award Recipient(s)
- University of Houston (PI: Choi, Yunsoo)