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Causal inference for time series
Many research questions in Earth and environmental sciences are inherently causal,
requiring robust analyses to establish whether and how changes in one variable cause …
requiring robust analyses to establish whether and how changes in one variable cause …
Discovering causal relations and equations from data
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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 …
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
Accurate forecasting of water quality variables in river systems is crucial for relevant
administrators to identify potential water quality degradation issues and take …
administrators to identify potential water quality degradation issues and take …
On the potential of Sentinel-2 for estimating Gross Primary Production
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 …
fundamental prerequisite for understanding and quantifying the terrestrial carbon cycle. Over …
Causal discovery in semi-stationary time series
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 …
assumption is a significant challenge. In practice, this challenge is common in many areas …