We assess evidence relevant to Earth's equilibrium climate sensitivity per doubling of
atmospheric CO2, characterized by an effective sensitivity S. This evidence includes …

There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

Equilibrium climate sensitivity, the global surface temperature response to CO doubling, has
been persistently uncertain. Recent consensus places it likely within 1.5–4.5 K. Global …

Abstract Machine learning approaches are increasingly used to extract patterns and insights
from the ever-increasing stream of geospatial data, but current approaches may not be …

Working Group I (WGI) of the Intergovernmental Panel on Climate Change (IPCC) assesses
the current evidence on the physical science of climate change, evaluating knowledge …

Climate change challenges societal functioning, likely requiring considerable adaptation to
cope with future altered weather patterns. Machine learning (ML) algorithms have advanced …

Data science models, although successful in a number of commercial domains, have had
limited applicability in scientific problems involving complex physical phenomena. Theory …

With accumulation of carbon cycle observations and model developments over the past
decades, exploring interannual variation (IAV) of terrestrial carbon cycle offers the …

Weather forecasting plays a fundamental role in the early warning of weather impacts on
various aspects of human livelihood. For instance, weather forecasting provides decision …

In recent years, an evaluation technique for Earth System Models (ESMs) has arisen—
emergent constraints (ECs)—which rely on strong statistical relationships between aspects …