Lead Performer: Argonne National Laboratory – Lamont, IL
Partner(s):
-- Oak Ridge National Laboratory – Oak Ridge, TN
-- Sandia National Laboratory – Albuquerque, NM
DOE Total Funding: $1,350,000
FY22 DOE Funding: $625,000
Cost Share: $0
Project Term: October 1, 2021 – December 31, 2023
Funding Type: Directed funding
Related Projects: EnergyPlus
Project Objective
Building energy modeling (BEM) is a key decision support tool for building energy efficiency and demand flexibility, supporting both design of new buildings and major retrofit and large-scale planning of codes and energy-efficiency programs. Weather data is a key input to BEM. Traditionally, BEM use cases have relied on weather data synthesized from historical record. A widely used set is Typical Meteorological Year 3 (TMY3) which is synthesized from data from the years 1993 to 2005. Sets such as TMYx incorporate data from as recently as 2018.
Unfortunately, historical data is unlikely to be representative of the type of weather a given building will experience throughout their lifetime, which is often 50 years and longer. Future weather will be increasingly warmer on average and humidity, cloud cover, and precipitation patterns are likely to change. Extreme events like storms and heat waves will also become more frequent, more pronounced, and longer in duration. To design buildings that will perform well into the future—and codes and programs that promote these buildings—models must incorporate our current best guesses of future weather, including extreme events.
The Intergovernmental Panel on Climate Change (IPCC) predicts future weather patterns using Global Climate Models (GCMs). These GCMs are evaluated against past climate data to instill confidence in future predictions and typically use ensembles to reduce bias. Though GCM results are available for download, global climate data is not directly usable for building energy simulation. This project will aggregate, process, and downscale future weather data from GCM results corresponding to multiple IPCC scenarios and make it usable by and available to building researchers, policy makers, and practitioners.
The project will be guided by an advisory group representing multiple sectors that will define, refine, and prioritize future weather data use cases that are most relevant to industry. The group will also help determine which weather files are produced and how they will be made available.
Project Impact
Weather is a key factor—perhaps the single most important exogenous factor—in determining a building’s energy performance and the health and safety of its occupants. Rapid and accelerating changes to the climate are making the design of buildings that maintain high energy performance, safety, and resilience throughout their lifetimes challenging. By developing usable and accessible weather data from the best-known current projections of global climate models, this project will support building practitioners, researchers, and policy makers in adopting a data-driven approach to making a key component of U.S. infrastructure, the national building stock, more resilient to climate change.
Contacts
Technology manager: Amir Roth, DOE
Principal investigator: Ralph Muehleisen, ANL