Climate services involve the generation, provision, and contextualization of information and
knowledge derived from climate research for decision making at all levels of society. These …

Climate projections continue to be marred by large uncertainties, which originate in
processes that need to be parameterized, such as clouds, convection, and ecosystems. But …

How clouds respond to warming remains the greatest source of uncertainty in climate
projections. Improved computational and observational tools can reduce this uncertainty …

We introduce generative models for accelerating simulations of high-dimensional systems
through learning and evolving their effective dynamics. In the proposed Generative Learning …

The social cost of carbon (SC-CO2) is an economic metric intended to provide a
comprehensive estimate of the net damages-that is, the monetized value of the net impacts …

Predictive simulations of complex systems are essential for applications ranging from
weather forecasting to drug design. The veracity of these predictions hinges on their …

Efforts to manage living marine resources (LMRs) under climate change need projections of
future ocean conditions, yet most global climate models (GCMs) poorly represent critical …

Informing the extensive preparations needed to manage climate risks, avoid damages, and
realize emerging opportunities is a grand challenge for climate change science. US …

An ultra-scalable fully-implicit solver is developed for stiff time-dependent problems arising
from the hyperbolic conservation laws in nonhydrostatic atmospheric dynamics. In the …

The best hope for reducing long-standing global climate model biases is by increasing
resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non …