Process-based modelling offers interpretability and physical consistency in many domains of
geosciences but struggles to leverage large datasets efficiently. Machine-learning methods …

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front
in terrestrial vegetation science, with emerging capability in space-based methodologies …

Abstract The Community Land Model (CLM) is the land component of the Community Earth
System Model (CESM) and is used in several global and regional modeling systems. In this …

Quantifying ecosystem carbon fluxes and stocks is essential for better understanding the
global carbon cycle and improving projections of the carbon-climate feedbacks. Remote …

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of
conventional space-agency-based platforms to include a plethora of sensing opportunities …

Quantifying global terrestrial photosynthesis is essential to understanding the global carbon
cycle and the climate system. Remote sensing has played a pivotal role in advancing our …

Representing unresolved moist convection in coarse‐scale climate models remains one of
the main bottlenecks of current climate simulations. Many of the biases present with …

Satellite-retrieved solar-induced chlorophyll fluorescence (SIF) has shown great potential to
monitor the photosynthetic activity of terrestrial ecosystems. However, several issues …

Land–atmosphere (LA) interactions are a main driver of Earth's surface water and energy
budgets; as such, they modulate near-surface climate, including clouds and precipitation …

Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate,
atmospheric composition, and land use. It is difficult to partition ecosystem-scale …