Research Highlights

 

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.

Recent Highlights

Cloud adjustments from large-scale smoke–circulation interactions affect marine cloud transitions

27 September 2022

Diamond, Michael S

Supported by: ARM ASR

Research area: Cloud-Aerosol-Precipitation Interactions

Our study combines insights from models at very different scales (regional climate and cloud-resolving) to distinguish between how smoke affects cloud transitions by changing the large-scale environment versus by seeding additional cloud particles and absorbing sunlight near the clouds.

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Identifying green vegetation variability over the Southern Great Plains

23 September 2022

Fast, Jerome D

Supported by: ARM ASR

Research area: Aerosol Processes

Large uncertainties persist in simulations of near-ground meteorological properties made using weather forecasting models associated with specifying surface properties, including the plant canopy. Scientists frequently derive details of the plant canopy for numerical weather prediction models using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. MODIS’s 500-meter resolution cannot resolve fine-scale [...]

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Quantifying the subgrid-scale variability in aerosol properties missing in models

22 September 2022

Fast, Jerome D

Supported by: ARM ASR

Research area: Aerosol Processes

A comprehensive suite of instruments was deployed on the Atmospheric Radiation Measurement (ARM) user facility's Gulfstream-1 aircraft to characterize aerosol properties over ARM's Southern Great Plains (SGP) site in north-central Oklahoma during the spring and late summer of 2016 as part of the Holistic Interactions of Shallow Clouds, Aerosols, and [...]

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New insights on the prevalence of drizzle in marine stratocumulus clouds

16 September 2022

zhu, zeen; Kollias, Pavlos

Supported by: ARM ASR

Research area: Cloud Processes

Detecting drizzle embryos is challenging for ground-based remote-sensing observations, which impedes our understanding of the precipitation process in marine stratocumulus clouds. A machine-learning-based approach is developed using unique radar Doppler spectra observations to identify the early stage of drizzle drops.

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Optimizing radar scan strategies for convective cell observations

13 September 2022

Oue, Mariko

Supported by: ASR

Research area: Cloud Processes

This study quantifies uncertainties in radar observations for convective cells and provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments, through the use of high spatiotemporal cloud-resolving model simulations coupled with a radar simulator and a cell-tracking algorithm.

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