READi Insights: Characterizing Discrepancies in Gridded Temperature Diurnal Cycles and Potential Consequences for Power System Planning

Gridded reanalysis products are widely used in energy system planning and operations to characterize long-term weather and extreme events. This study evaluates how three widely-used reanalysis products (ERA5, ERA5-Land, and MERRA2) capture the magnitude, timing, and shape of daily temperature cycles across the contiguous United States compared to in-situ station observations from 2000–2022. Results show that while bias correction can reduce some of the bias in gridded temperatures, discrepancies in the timing and shape of daily temperature extrema often remain. For example, ERA5, exhibits a 1–2 hour lag in the occurrence of daily extrema, most pronounced in winter and for western mountainous regions. While ERA5 generally shows the closest agreement with station observations in capturing the shape of hourly temperature around extrema, ERA5-Land and MERRA2 match observations more closely at many locations. These timing and shape discrepancies have direct implications for load forecasting, peak demand estimation, and grid flexibility requirements. We recommend that energy system practitioners carefully validate reanalysis datasets using metrics specific to their applications and regions before integration into planning and operational models.