Compute Diagnostics for Precipitation Quantile Mapping

Computes diagnostics comparing reference and quantile-mapped precipitation series. Reports moment changes, quantiles, tail metrics, dry/wet-day frequencies, spell lengths, and optional temporal/monthly patterns. When `mean_factor`/`var_factor` are provided together with `month` and `year`, moment and monthly diagnostics are compared against the intended perturbations (scenario-aware null hypothesis).

Usage

diagnose_precip_qm(
  precip_ref,
  precip_adj,
  month = NULL,
  year = NULL,
  mean_factor = NULL,
  var_factor = NULL,
  wet_thresh = 0.1,
  probs = c(0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.99)
)

Arguments

precip_ref

Numeric vector. Reference (original) precipitation values.

precip_adj

Numeric vector. Adjusted precipitation values (same length as `precip_ref`).

month

Integer vector (optional). Month index (1–12) for each observation.

year

Integer vector (optional). Year index (1..n_years) for each observation.

mean_factor

Numeric matrix (optional). Target mean scaling factors (n_years x 12).

var_factor

Numeric matrix (optional). Target variance scaling factors (n_years x 12).

wet_thresh

Numeric. Threshold for defining wet days (default = 0.1 mm).

probs

Numeric vector. Quantile probabilities to evaluate.

Value

A list of class `precip_qm_diagnostics` with elements:

• `moments`: moment diagnostics table

• `quantiles`: quantile comparison table

• `extremes`: tail metrics table

• `temporal`: temporal metrics table (optional)

• `monthly`: month-by-month diagnostics table (optional)

• `spells`: wet/dry spell diagnostics table

• `drydays`: wet/dry frequency diagnostics table

• `summary`: compact summary list