Highlights will be written for high-level accomplishments and published journal articles of ASR research. Each ASR principal investigator (PI) is expected to submit at least one highlight per fiscal year.
Research Highlights
Recent Highlights
Chemical properties and single-particle mixing state of soot aerosol in Houston during TRACER
1 May 2024
Zhang, Qi
Supported by:
Research area: Aerosol Properties
Our comprehensive measurements of black carbon (BC)-containing aerosols, conducted during the TRACER campaign, provided detailed insights into the composition, behavior, and variability of soot aerosols in Houston. We find that the coating thickness of individual BC particles and their mixing with other species vary significantly, influenced by diverse emission sources [...]
Above-cloud concentrations of cloud condensation nuclei help to sustain some arctic low-level clouds
24 April 2024
Igel, Adele
Supported by:
Research area: Cloud-Aerosol-Precipitation Interactions
We investigated the importance of aerosol particles above cloud top for maintaining low-level clouds in the Arctic.
Are atmospheric models too cold in the mountains? The state of science and insights from SAIL
20 April 2024
Feldman, Daniel
Supported by:
Research area: Atmospheric Thermodynamics and Vertical Structures
We reviewed the peer-reviewed literature, and found that many types of high-resolution atmospheric models produce surface air temperatures that are colder than what is observed in high-altitude complex terrain. We evaluate the possible causes of this bias, and also examine data using three different high-resolution models and data collected by [...]
Relationships between cloud and land surface fluxes across cumulus and stratiform coupling
12 April 2024
Su, Tianning; Li, Zhanqing
Supported by:
Research area: Cloud Processes
In our study, we systematically explored the multifaceted relationships between land surface fluxes and low-cloud formation across different cloud regimes. By analyzing merged data of the long-term ARM ground observations with coupling diagnostics, we identified distinct cloud-land interaction patterns contingent upon different coupling regimes and critically assessed the capabilities of [...]
Interpretable and physics-aware neural networks improve modeling of turbulence near the surface
22 March 2024
Ovchinnikov, Mikhail; Wang, Aaron
Supported by:
Research area: Atmospheric Thermodynamics and Vertical Structures
Turbulence near the Earth’s surface effectively transports momentum, heat, and moisture into the atmosphere. However, a universal model to accurately represent these turbulent fluxes in various flows does not exist. When the turbulence is driven by a vertical temperature gradient and thermal convection, as in the Rayleigh-Bénard convection, traditional turbulence [...]