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Publication Date
18 February 2021

Better Modeling of Cloud Properties Shows Aerosol-Cloud-Interactions’ Influence on Convective Clouds

A physically-advanced modeling scheme shows that anthropogenic aerosols significantly enhance the convective intensity and precipitation of storms.
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Aerosols can increase the convective intensity and precipitation associated with storms in the Houston area.

The impacts of aerosol-cloud interactions (ACI) on weather and climate remain largely uncertain. The simple representations of cloud microphysical processes, like droplet condensational growth and evaporation, contribute to this uncertainty. More accurate physically-advanced bin schemes are too computationally expensive for standard weather and climate prediction, but better represent cloud microphysics and ACIs. Researchers employed a commonly used bulk scheme and a physically-advanced bin scheme coupled with the Chemistry version of the Weather Research and Forecast model (WRF-Chem) to investigate their impacts on simulating how anthropogenic aerosols affect deep convective clouds. They found that the detailed bin scheme simulated the observed storm well and the anthropogenic aerosols invigorated convective intensity and precipitation.


The large uncertainties in ACI representations contribute to the large uncertainty in weather and climate predictions. This work identifies a significant deficiency in the bulk scheme commonly used in weather and climate models to simulate ACI and presents an approach to fix the problem–employing a physics-based calculation for droplet condensation and evaporation. This allows researchers to use the newly modified bulk scheme to simulate ACI more realistically without adding additional time to the calculations.


Researchers investigated the impacts of anthropogenic aerosols on the convective intensity and precipitation of a thunderstorm that occurred over Houston on June 19, 2013. They employed WRF-Chem coupled with either the commonly used two-moment bulk microphysics scheme or a physically-advanced bin scheme at high resolution (0.5 km). First, the researchers evaluated observation-based simulations of aerosol, radar reflectivity, and precipitation properties. The researchers then carried out model sensitivity tests with the different cloud microphysics schemes and compared model performance simulating the deep convective clouds and the anthropogenic aerosol effects on the simulated storm. They found that the physically-advanced bin scheme simulates a storm in good agreement with observations. It also shows that anthropogenic aerosols notably enhance convective intensity and precipitation; this is mainly attributed to the increased condensation and ice-related latent heating. In contrast, the commonly used bulk scheme simulates a storm with negligible aerosol effects that does not agree with observations, mainly due to the unphysical representations of droplet condensational growth and evaporation. By using a physics-based approach to explicitly simulate condensation and evaporation, the modified bulk scheme shows similar effects on the convective intensity as the bin scheme. These results show that physically representing droplet condensational growth and evaporation is very important for simulating ACI in models.

Point of Contact
Jiwen Fan
Pacific Northwest National Laboratory (PNNL)
Funding Program Area(s)