Observationally driven Resource Assessment with CoupLEd models (ORACLE)

Dataset · Sat Sep 30 00:00:00 EDT 2023

DOI:https://doi.org/10.25584/oracle/2005178· OSTI ID:2005178

Krishnamurthy, Raghu ^[1]; Ghate, Virendra ^[2]; Haupt, Sue Ellen ^[3]; Churchfield, Matthew ^[4]; Mirocha, Jeff ^[5]

---

1. Battelle Pacific Northwest Labs., Richland, WA (United States); Battelle - Pacific Northwest National Laboratory
2. Argonne National Laboratory (ANL), Argonne, IL (United States)
3. University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States)
4. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
5. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

This project seeks to carry out a multifaceted analysis combining buoy observations, machine learning, turbulence, satellite data and high-resolution modeling. Our analyses will investigate air–sea interaction physics governing the variation of the winds with height and influence of clouds, uncertainty in coupled ocean-wave-atmosphere mesoscale models to capture certain key atmospheric phenomenon observed over the U.S. West Coast, impact of climate change, and the fidelity with which resource characterization models describe the range of observed offshore wind conditions. This project will focus its efforts on characterizing and assessing the atmospheric and oceanographic conditions along the U.S. West Coast.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
• OSTI ID: 2005178
• Country of Publication: United States
• Language: English

Related Subjects

Wind
Energy