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Climate

Tracing the space-time causal origins of Earth system extremes

Jhayron S. Pérez-Carrasquilla, J. Jake Nichol, Vanessa Robledo, Diana Bull, Katherine Dagon, Michael N. Evans, Maria J. Molina

Featured July 15, 2026

Original Paper

AI-generated analysis — This is SciGrove's AI interpretation of the paper, not peer-reviewed content. Always refer to the original paper.

Simply

A new method called TraCE-ST acts like a detective, tracing backward in time through weather data to find out exactly which past events and locations caused a big storm or heatwave, even showing how much each factor contributed.

In depth
The paper introduces TraCE-ST (Tracer of Causal Evolutions in Space and Time), a novel framework that traces event-conditioned causal pathways in multivariate gridded Earth system data. It leverages existing local causal discovery methods but extends them into a Lagrangian-inspired approach to identify multi-step, multi-variable causal chains leading to extreme events, and probabilistically estimates the relative contributions of different drivers.

Key Takeaways

  • 1
    Introduces TraCE-ST, a probabilistic Lagrangian-inspired framework for tracing event-conditioned causal pathways in high-dimensional Earth system data.
  • 2
    Enables the identification of multi-step, multi-variable causal chains leading to extreme events, moving beyond local causal links to dynamic, event-centered explanations.
  • 3
    Quantifies the relative causal contributions of co-occurring and competing drivers through an ensemble-based probabilistic formulation, providing robust insights into complex phenomena.

Conceptual Flow

HIGH LEVEL
1
Methodology: Tracing Causal Paths

The method starts with a big event, then looks backward step-by-step to find what caused it, like following a trail.

Big Event
Trace Backwards
Past Cause 1
Past Cause 2
Past Cause 3
2
Results: Uncovering Multiple Drivers

It shows that big events often have many causes, and it can tell you which causes were most important.

Cause A
Cause B
Cause C
Combine & Influence
Big Event

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