Causal Directions Matter: How Environmental Factors Drive Convective Cloud Detrainment Heights
Abstract This study investigates how environmental factors influence the level of maximum detrainment (LMD) in deep convective clouds. Through a novel application of the Linear Non‐Gaussian Acyclic Model (LiNGAM), we discover causal structures between environmental variables and LMD, observed at six...
Saved in:
| Main Authors: | Dié Wang, Simon Lee, Tao Zhang, Christian Lackner, Daniel Kirshbaum, Michael Jensen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-07-01
|
| Series: | Geophysical Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2025GL114941 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Estimation of Entrainment and Detrainment Rates in Cumulus Clouds Using Global Satellite Observations
by: Lei Zhu, et al.
Published: (2025-02-01) -
CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification—leveraging deep learning models for enhanced diagnostic accuracy
by: Zahra Taghados, et al.
Published: (2025-04-01) -
Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models
by: Mi Jin Noh, et al.
Published: (2025-01-01) -
Causality, Machine Learning, and Feature Selection: A Survey
by: Asmae Lamsaf, et al.
Published: (2025-04-01) -
Connections matter: Updraft merging in organized tropical deep convection
by: I. B. Glenn, et al.
Published: (2017-07-01)