eames_temperature() creates a temperature-only future-EPW method using the
monthly temperature signal and bounded temperature weighted stretch (BTWS)
described by Eames et al. (2024). Matching historical and future daily
tas, tasmin, and tasmax inputs are required.
The daily CMIP6 inputs are aggregated into 12 calendar-month values for mean temperature, average daily minimum temperature, and average daily maximum temperature. One future-minus-historical set is applied to every baseline day in that EPW month before BTWS reconstructs the hourly profile. The method therefore does not use daily-varying change factors.
The published method used monthly UKCP18 factors. This implementation adapts its temperature calculation to monthly statistics derived from daily CMIP6 data. It retains epwshiftr's specific-humidity closure and EPW output policy, and does not implement the paper's non-temperature transformations.
eames_temperature(reference = NULL)A required historical_reference(),
shift_reference_plan(), or extracted ShiftClimate stage.
A complete ShiftMorphMethod for shift_future_epw().
Eames, M. E., Ramallo-González, A. P., and Wood, M. J. (2024). A revised morphing algorithm for creating future weather for building performance evaluation. doi:10.1177/01436244231218861