hourly_kernel_qdm() creates a complete multi-year future-weather method from matching three-hourly historical and future model data plus an hourly observed reference. CMIP6 model roles require point-sampled 3hrPt tas, ps, huss, uas, and vas, together with interval-mean 3hr rsds and rsdsdiff. Daily tasmin and tasmax are optional interpolation anchors. The observed role requires tas, ps, hurs, sfcWind, rsds, and rsdsdiff.

Continuous model state variables and wind-vector components are interpolated to an hourly lattice. Relative humidity is derived from huss, tas, and ps; scalar speed and meteorological direction are derived from uas and vas. Shortwave variables are allocated with solar geometry before the centered three-month kernel-density Quantile Delta Mapping calculation. Every corrected future-model year is then mapped to the 365-day EPW calendar and passed through the common absolute_model_fields physical policy, with the future model's wind direction retained alongside the corrected speed.

The method returns one addressable output member per complete future-model year. Numerical kernel, bandwidth, grid, tail, and zero-denominator settings not reported by the source publication remain explicit experimental defaults. The high-level workflow expands historical and future extraction windows by one source timestep so bounded interpolation can retain every requested year. Pre-extracted ShiftClimate inputs must retain equivalent edge support.

hourly_kernel_qdm(
  reference = NULL,
  observed_reference = NULL,
  signal_overrides = list()
)

Arguments

reference

A required historical_reference(), shift_reference_plan(), or extracted ShiftClimate stage containing matching variable-specific 3hrPt, 3hr, and optional daily historical model output.

observed_reference

A required shift_reference_plan() or extracted ShiftClimate stage containing hourly observed weather.

signal_overrides

Optional named list of variable-specific kernel-QDM settings passed to the signal component.

Value

A complete ShiftMorphMethod for shift_future_epw().

References

Wang, Z. et al. (2023). Climate data for building simulations in EnergyPlus. doi:10.1038/s41467-023-41458-5