This project will focus on developing, evaluating, and using a range of modeling tools to systematically analyze coastal processes, stressors, responses, and uncertainties, with an emphasis on: Interactions across different parts of coastal systems; Long-term changes in the coastal environment; and...
Multiple federal government agencies have mission elements that address national needs related to water and advance the underlying science. These diverse mission and scientific needs have engendered a large base of water-related data and modeling capabilities that, while useful for their intended...
Spruce and Peatlands Responses Under Changing Environments (SPRUCE) site is the 8.1-ha S1 bog, a Picea mariana [black spruce] – Sphagnum spp. ombrotrophic bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Two field research...
The Community Emissions Data System (CEDS) produces emissions anthropogenic aerosol and precursor compounds over the entire industrial era, from 1750 to the present for use in global Earth system models and Earth system research more broadly. Emissions are produced at the country level by fuel and...
The long term goal of this scientific focus area (SFA) is to transform our understanding of climate-relevant processes and provide more robust model representations of the climate system through the integration of new knowledge on cloud and aerosol populations, and their interactions with each other...
Predictive Phenomics is addressing the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems .
The science objectives of this project are to: Functionally enrich microbial communities and generate multi-omics to correlate biochemical mechanisms to activity. Integrate PhenoProfiling with Thrust Areas 2 and 3 to develop models for phenotype prediction and interspecies interactions. Evaluate...
The Human Islet Research Network (HIRN) is a large consortia with many research projects focused on understanding how beta cells are lost in type 1 diabetics (T1D) with a goal of finding how to protect against or replace the loss of functional beta cells. The consortia has multiple branches of...
Machine learning is a core technology that is rapidly advancing within type 1 diabetes (T1D) research. Our Human Islet Research Network (HIRN) grant is studying early cellular response initiating β cell stress in T1D through the generation of heterogenous low- and high-throughput molecular...
PNNL’s Vision Statement for Equity in the Power Grid Drawing from a wealth of interdisciplinary research in grid modernization, PNNL is spearheading an effort to advance equity and energy justice through the role of scientific research with the goal of building an advanced national power grid...
