Discovering Macro- and Micro-Physical Relations in Precipitation Efficiency and Aerosol Wet Scavenging in Warm Clouds Using ARM Observation-Model Data Cubes and Machine Learning
Principal Investigator
Christine Chiu
— Colorado State University
Co-Investigators
| Shu-Hua Chen — University of California Davis | Peter Jan Peter Jan — Colorado State University |
| Sonia Kreidenweis — Colorado State University | V. Chandrasekar — Colorado State University |
Abstract
Marine boundary layer clouds are a key contributor to the Earth’s albedo. An increase in aerosol loading could reduce drizzle production, modulate the stability of the boundary layer, and change cloud properties, lifetime, and extent. Apart from the impact of aerosol on cloud and precipitation, it is equally important to understand the impact of cloud and precipitation on aerosol. Aerosols can be scavenged due to nucleation, impaction by cloud droplets, and washing out by falling raindrops. These processes are the dominant loss mechanisms in the aerosol life cycle. Since the wet scavenging of aerosol tightly relates to precipitation efficiency, the understanding of the aerosol wet scavenging process relies on our understanding of aerosol activation to drops and the subsequent precipitation formation processes.
However, many global weather and climate models continue to produce rain too frequently over oceans with incorrect intensity. Even with the same precipitation intensity, the wet scavenging rate below cloud derived from theoretical models can be 1–2 orders of magnitude smaller compared to those from observational-based empirical relationships. In principle, the precipitation efficiency of warm clouds closely connects with cloud properties, in-cloud contact time, the time scale of cloud lifetime, and thus precipitation susceptibility and probability. However, up to now, there is no known relation for describing macro- and micro-physical relations in precipitation and aerosol wet scavenging efficiency.
The goal of the project is to discover scaling relations that will advance our understanding of how cloud microphysical processes and large-scale environments collectively determine precipitation efficiency, its relationship with aerosol wet scavenging processes, and its impact on aerosol budget and distribution. To achieve this goal, we will focus on measurements from the ARM Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) and pursue the following objectives:
- Build ARM observation-model data cubes.
- Discover the equations that describe the scaling relations in precipitation and aerosol scavenging efficiency from data cubes.
- Characterize the diurnal and seasonal variability of precipitation and aerosol wet scavenging efficiencies.
Results from the project will help answer how precipitation and aerosol wet scavenging evolve and determine the spatial distribution and variability of aerosol fields. The research, will for the first time, provide the equations that represent the most essential relations of precipitation and aerosol wet scavenging processes with cloud properties and large-scale dynamics and thermodynamics. Discovering such scaling relations is a huge step forward in the basic understanding of the processes involved. The newly discovered equations can also serve as a new metric for assessing weather and climate simulations to identify model deficiencies.