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Seasonal climatology for one or more measurement types

Source: R/transect.R
cc_climatology.Rd

A baseline per (grid_key, depth bin, month), which is the finest grouping the CalCOFI sampling design supports: quarterly-ish cruises over decades give many years per calendar month at a station, but not many days.

Usage

cc_climatology(
  con,
  variables = "temperature_ave",
  years = c(1993, 2013),
  dataset_key = "calcofi_ctd-cast",
  depth_max = 500,
  depth_bin = 5,
  min_n = 3
)

Arguments

con

DuckDB connection to a release.

variables

measurement_types.

years

two-element baseline range, inclusive, e.g. c(1993, 2013). Recorded on the result as the baseline attribute so a plot can state it.

dataset_key, depth_max, depth_bin

as in cc_transect_section().

min_n

minimum observations for a cell to be returned (default 3).

Value

Tibble: grid_key, month, depth_m, variable, clim_mean, clim_sd, clim_n; with attribute baseline.

Details

Deliberately a plain monthly mean, not a harmonic fit. Rudnick et al. (2017) fit annual and semiannual harmonics for the CUGN glider climatology, which suits near-continuous glider sampling; CalCOFI's is episodic and unevenly spaced, and a monthly mean is both defensible and legible — someone reading an anomaly can say exactly what it is a departure from. n is returned so a thin cell can be filtered rather than silently trusted.