Causal inference for time series

J Runge, A Gerhardus, G Varando, V Eyring… - Nature Reviews Earth & …, 2023 - nature.com
Many research questions in Earth and environmental sciences are inherently causal,
requiring robust analyses to establish whether and how changes in one variable cause …

Discovering causal relations and equations from data

G Camps-Valls, A Gerhardus, U Ninad, G Varando… - Physics Reports, 2023 - Elsevier
Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …

Rising water-use efficiency in European grasslands is driven by increased primary production

C Poppe Terán, BS Naz, A Graf, Y Qu… - … Earth & Environment, 2023 - nature.com
Water-use efficiency is the amount of carbon assimilated per water used by an ecosystem
and a key indicator of ecosystem functioning, but its variability in response to climate change …

Causally‐informed deep learning to improve climate models and projections

F Iglesias‐Suarez, P Gentine… - Journal of …, 2024 - Wiley Online Library
Climate models are essential to understand and project climate change, yet long‐standing
biases and uncertainties in their projections remain. This is largely associated with the …

Browning of vegetation in efficient carbon sink regions of India during the past two decades is driven by climate change and anthropogenic intrusions

R Kashyap, J Kuttippurath, P Kumar - Journal of Environmental …, 2023 - Elsevier
Accurate estimation of carbon cycle is a challenging task owing to the complexity and
heterogeneity of ecosystems. Carbon Use Efficiency (CUE) is a metric to define the ability of …

Decoupling between ecosystem photosynthesis and transpiration: a last resort against overheating

C Krich, MD Mahecha, M Migliavacca… - Environmental …, 2022 - iopscience.iop.org
Ecosystems are projected to face extreme high temperatures more frequently in the near
future. Various biotic co** strategies exist to prevent heat stress. Controlled experiments …

Research on delay propagation mechanism of air traffic control system based on causal inference

L Zeng, B Wang, T Wang, Z Wang - Transportation Research Part C …, 2022 - Elsevier
In the air traffic control (ATC) system, delays are tightly coupled among airports.
Understanding the interactions of these delays is a prerequisite for accurate prediction …

A new framework for water quality forecasting coupling causal inference, time-frequency analysis and uncertainty quantification

C Zhang, X Nong, K Behzadian, LC Campos… - Journal of …, 2024 - Elsevier
Accurate forecasting of water quality variables in river systems is crucial for relevant
administrators to identify potential water quality degradation issues and take …

On the potential of Sentinel-2 for estimating Gross Primary Production

DE Pabon-Moreno, M Migliavacca… - … on Geoscience and …, 2022 - ieeexplore.ieee.org
Estimating gross primary production (GPP), the gross uptake of CO 2 by vegetation, is a
fundamental prerequisite for understanding and quantifying the terrestrial carbon cycle. Over …

Causal discovery in semi-stationary time series

S Gao, R Addanki, T Yu, R Rossi… - Advances in Neural …, 2023 - proceedings.neurips.cc
Discovering causal relations from observational time series without making the stationary
assumption is a significant challenge. In practice, this challenge is common in many areas …