What is it about?
This dataset contains fTMY fi les for 3281 US Counties in the continental United States. The data for each county is derived from six different global climate models (GCMs) from the 6th Phase of Coupled Models Intercomparison Project CMIP6-ACCESSCM2, BCC-CSM2-MR, CNRM-ESM2-1, MPI-ESM1-2-HR, MRI-ESM2-0, NorESM2-MM.
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Why is it important?
As global emissions and temperatures continue to rise, global climate models offer projections as to how the climate will change in years to come. These model projections can be used for a variety of end-uses to better understand how current systems will be affected by the changing climate. While climate models predict every individual year, using a single year may not be representative as there may be outlier years. It can also be useful to represent a multi-year period with a single year of data. Both items are currently addressed when working with past weather data by a using Typical Meteorological Year (TMY)methodology. This methodology works by statistically selecting representative months from a number of years and appending these months to achieve a single representative year for a given period. In this analysis, the TMY methodology is used to develop Future Typical Meteorological Year (fTMY) using climate model projections. The resulting set of fTMY data is then formatted into EnergyPlus weather (epw) fi les that can be used for building simulation to estimate the impact of climate scenarios on the built environment.
Perspectives
In the realm of building energy simulation, the capacity to accurately project future energy requirements is paramount. The introduction of the future Typical Meteorological Year (fTMY) EPW weather files, as outlined in this research, heralds a transformative era for the Building Energy Simulation community.
Fengqi Li
Oak Ridge National Laboratory
Read the Original
This page is a summary of: Multi-Model Future Typical Meteorological (fTMY) Weather Files for nearly every US County, November 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3600100.3626637.
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