PNNL is contributing analytics expertise to a first-of-its-kind electric vehicle carsharing program in rural Hood River, Oregon.

A report on the projected effects of climate change on federal hydropower through the end of the twenty-first century.

The Data-Model Convergence (DMC) Initiative is a multidisciplinary effort to create the next generation of scientific computing capability through a software and hardware co-design methodology.

New report examining multiple decades of climate and hydropower generation data provides insights into resilience of the western hydropower fleet.

PNNL partners with agencies and industry to identify and engage historically disadvantaged populations in regulatory decision-making, environmental assessment, and impact estimation of the consequences of complex polices and projects.

Usable and explainable models for global-scale, cross-lingual proliferation expertise identification and forecasting.

GODEEEP is an internal PNNL Agile investment inspired that addresses U.S. priorities related to clean energy and environmental and energy equity.

A new set of resources from PNNL helps guide dam owners and operators through response and recovery actions in the wake of cybersecurity or unusual incidents.

HydroWIRES initiative helps water stakeholders reap the full benefit of hydropower’s superpower: versatility

Researchers are bridging hydropower data gaps for unrivaled forecasting precision to support grid resilience.

By improving the Weather Research and Forecasting (WRF)-Solar model, this project aims to reduce forecast errors, improve sub-grid scale variability estimates, and more accurately estimate forecast uncertainty.

PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.

The Pacific Northwest National Laboratory is developing a Port Electrification Handbook—a reference to aid maritime ports nationwide in their clean energy transition.

PREPARES demonstrates linkages between climate or weather conditions and human domain systems by combining quantitative geophysical data with qualitative data.