Land surface models (LSMs) are a vital tool for understanding, projecting, and predicting the
dynamics of the land surface and its role within the Earth system, under global change …

The land surface models that provide surface fluxes of energy and mass to the atmosphere
in weather forecast and climate models typically represent plant canopies as a homogenous …

Terrestrial ecosystems are essential for food and water security and CO2 uptake. Ecosystem
function is dependent on the availability of soil moisture, yet it is unclear how climate change …

This paper is derived from a keynote talk given at the Google's 2020 Flood Forecasting
Meets Machine Learning Workshop. Recent experiments applying deep learning to rainfall …

In the atmosphere, microphysics refers to the microscale processes that affect cloud and
precipitation particles and is a key linkage among the various components of Earth's …

The goal of this commentary is to critically evaluate the use of popular performance metrics
in hydrologic modeling. We focus on the Nash‐Sutcliffe Efficiency (NSE) and the Kling …

Abstract Information about the spatiotemporal variability of soil moisture is critical for many
purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction …

Accurately predicting weather and climate in cities is critical for safeguarding human health
and strengthening urban resilience. Multimodel evaluations can lead to model …

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 …

The increasing complexity of Earth system models has inspired efforts to quantitatively
assess model fidelity through rigorous comparison with best available measurements and …