Climate Analytics to Support Natural Gas Sector Utilities: Actionable, Responsive and Open Solutions for Historical Climate Needs in California
Develops a platform serving weather-related data to support natural gas sector resiliency, including continuously updated weather observations, remote sensing, and reanalysis data based on advanced statistical techniques.
The research team worked with CEC staff on strategies for engaging key stakeholders, including CPUC staff involved with long-term gas planning rulemaking. The team is continuing to coordinate with and leverage the architecture of a data platform being developed under EPIC-funded grant EPC-20-007. Work continues along the two main project focuses: (1) Assessing climate implications for reliability planning for fossil gas; and (2) Producing hourly quality-controlled versions of hourly weather data. As of July 2022, for Focus 1, the project team organized, facilitated, and analyzed working group discussions with gas and other energy industry stakeholders toward understanding and serving their specific weather-data needs and concerns. For Focus 2, the project team has produced a series of quality-controlled weather data sets including those required by related EPIC grants, developed protocols for Quality Assurance/Quality Control and data formatting, identified best practices and metadata standards, and analyzed available hourly data by variable and data source. Converting quality assurance and control processes to be fully cloud-based is underway. This project supports research efforts under California's Fifth Climate Change Assessment.
Recipient will produce a data assimilation platform that serves as a central location for weather-related data of interest to natural gas stakeholders. The platform will provide continuously updated weather observations, remote sensing, and reanalysis data that support natural gas sector adaptation and resiliency. This data assimilation platform will be extended to generate value-added data products, such as risk from landslides triggered by extreme precipitation in areas severely impacted by wildfire. These value-added products will provide insights into climate-natural gas system dynamics. The data assimilation platform will enable data produced by other CEC-funded research to be made available quickly, with lower costs to ratepayers. The project will use machine learning and advanced statistical techniques using open source software to bring big-data, intelligent computing techniques to climate resilience planning problems in the natural gas system.
The design and implementation of this work will ensure that historical climate data of relevance to natural gas sector planning can be continuously updated and maintained at a low cost to ratepayers.