How key features of early development shape deep convective systems.

Area of Science:

• Atmospheric Science
• Climate Science
• Meteorology

Background:

• Deep Convective Systems (DCSs) are crucial for tropical precipitation and radiation budget.
• Understanding DCS growth factors and future behavior in a warming climate is a fundamental challenge.
• Previous research focused on environmental controls or idealized internal dynamics, lacking a clear understanding of their relative roles.

Purpose of the Study:

• To quantitatively assess the relative influence of internal versus external factors on the mature cloud shield size of DCSs.
• To determine the key predictors of DCS mature size throughout their development.
• To investigate the dominance of intrinsic properties versus environmental conditions in controlling DCS size.

Main Methods:

• Utilized the high-resolution global SAM simulation from the DYAMOND project.
• Employed TOOCAN Lagrangian tracking for DCS identification and analysis.
• Applied machine learning tools to analyze system growth and influencing factors.

Main Results:

• System growth rate in the first 2 hours predicts final size (r=0.65).
• Beyond 2 hours, growth rate is the strongest predictor of DCS size.
• Early DCS development is influenced by ice water path heterogeneity, migration, neighboring systems, and deep shear.

Conclusions:

• System-intrinsic properties have a stronger influence on mature DCS size than environmental conditions.
• The initial environment does not strictly constrain the final size of DCSs.
• Internal dynamics become dominant in determining the size of larger DCSs.