Observing Aerosol Primary Convective Invigoration and Its Meteorological Feedback

Aerosols can invigorate deep convective clouds (DCCs) directly by nucleating more cloud droplets, named as Primary Aerosol Convective Invigoration (PAI). However, the covarying Meteorology-Aerosol Invigoration (MAI) effect on DCC has been a long-standing issue in quantifying PAI's contribution. Here, observations show that PAI causes positive feedback from DCC to meteorology, further invigorating DCC through enhanced humidity, updraft and destabilization, thereby adding to MAI. Further, PAI is separated from MAI observationally by quantifying the sensitivity of DCC properties to aerosol changes under fixed meteorology through the artificial neural network. When fine aerosol changes from the cleanest to optimal concentration (5 & mu;g m(-3)), PAI contributes 72% & PLUSMN; 2% of the total aerosol-associated cloud top cooling by 12 & DEG;C, 42% & PLUSMN; 4% of the 30% prolonged lifetime, and 50% & PLUSMN; 4% of the more than doubled rainfall. This result underlines the comparable magnitudes of PAI and MAI, which have not been considered until now in weather and climate prediction.

Automated summary

Aerosols have the ability to directly invigorate deep convective clouds (DCCs) by nucleating more cloud droplets, which is known as Primary Aerosol Convective Invigoration (PAI). However, the covarying Meteorology-Aerosol Invigoration (MAI) effect on DCCs has been a long-standing issue in quantifying the contribution of PAI. Observations show that PAI causes a positive feedback from DCCs to meteorology, further enhancing DCCs through increased humidity, updraft, and destabilization, thus contributing to MAI. The study also separates PAI from MAI through observational quantification of the sensitivity of DCC properties to aerosol changes under fixed meteorology using artificial neural networks.