Actionable climate science entails the provision of local-to-regional scale climate information to support decision-making regarding climate impacts, adaptation and mitigation. Despite advances in theories, observations, climate modeling techniques, and high performance computing, large...

This project is an interdisciplinary collaboration supported by US DOE Office of Science's Scientific Discovery through Advanced Computing (SciDAC) program. The project addresses a crucial but largely overlooked source of error in the Energy Exascale Earth System Model (E3SM) and other atmosphere...

This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.

The PNNL-SERDP database was constructed by PNNL to generate the quantitative infrared spectra of gases associated with biomass burning; the reference data are to allow detection and quantification of such gases via infrared absorption spectroscopy. Candidates for the database were selected based on...

The Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) database was generated to mechanistically understand how feedbacks across scales, from molecular to plant to plant populations and communities to ecosystems, govern the resilience of system functions to elevated CO2...

The EyeSea underwater video dataset was assembled for developing algorithms for detecting fish in real world underwater video data. The data were recorded as part of environmental monitoring efforts at three different water power sites.

The objective of Terrestrial-Aquatic Interface (TAI) research in PREMIS is to understand the factors governing C and nutrient movement and transformation through the TAI, and their sensitivities to inundation and salinity within coastal watersheds.

Accurate characterization of the global downward shortwave (SW) and photosynthetically active radiation (PAR) is fundamental for Earth system modeling and global change research. Combined with a machine-learning method, we used the Earth Polychromatic Imaging Camera (EPIC) data onboard the Deep...

The VAST Challenge 2019 presents three mini-challenges and a grand challenge for you to apply your visual analytics research and technologies to help a city grapple with the aftermath of an earthquake that damages their nuclear power plant. These challenges are open to participation by individuals...

The long-term goals of this scientific focus area (SFA) are to develop flexible and extensible modeling capabilities that capture the dynamic multiscale interactions among climate, energy, water, land, socioeconomics, critical infrastructure, and other sectors and to use these capabilities to study...

This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities. This data was generated by PNNL. Activities can be phone calls, transactions, or any other type of communications. Most of...

Neisseria gonorrhoeae is a Gram-negative diplococcus that is responsible for the sexually transmitted infection gonorrhea, a high morbidity disease in the United States and worldwide. Over the last several years N. gonorrhoeae strains resistant to antibiotics used to treat this infection have begun...

This dataset was collected from PNNL operated buildings utilizing the PNNL developed open source platform, VOLTTRON in conjunction with PNNL Facilities and Operations staff. VOLTTRON provides an environment for buildings researchers to deploy applications interacting with building management systems...

Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson PerCon SFA Project Publication Experimental Data Catalog The Persistence Control of Engineered Functions in Complex Soil Microbiomes Project (PerCon SFA) at Pacific Northwest National Laboratory ( PNNL ) is a Genomic Sciences Program...

The Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...