PNNL

A perspective on lessons learned and future needs for wind energy field campaigns

Exposing Process-Level Biases in a Global Cloud Permitting Model with ARM Observations

Physical and Hydraulic Properties of RCRA Borehole Samples from the Hanford Site : Final Report, Fiscal Years 2023-2024

AI Improves the Accuracy, Reliability, and Economic Value of Continental-Scale Flood Predictions

Opening doors to physical sample tracking and attribution in Earth and environmental sciences

Spatially varying seasonal modulation to tidal stream energy potential due to mixed tidal regimes in the Aleutian Islands, AK

Why April Stands Out: Monthly Impacts of Internal Variability on Arctic Amplification

Two PNNL Researchers Win DOE Early Career Research Awards

From studying the multisector ripple effects of extreme events to exploring the chemical reactions that underlie life on Earth, two up-and-coming PNNL scientists were recognized for their scientific vision and prowess.

Artificial Intelligence for Subsurface Geophysical Imaging and Mineral Exploration

RemPlex Seminar: Data Readiness for AI Applications in Environmental Remediation

A panel of data scientists shares approaches for extracting, cleaning, and preparing data for environmental remediation applications of artificial intelligence, machine learning, and large language models.