CST_RFTemp {CSTools}

Temperature downscaling of a CSTools object using lapse rate correction or a reference field

Description

This function implements a simple lapse rate correction of a temperature field (an object of class 's2dv_cube' as provided by 'CST_Load') as input. The input lon grid must be increasing (but can be modulo 360). The input lat grid can be irregularly spaced (e.g. a Gaussian grid) The output grid can be irregularly spaced in lon and/or lat.

Usage

CST_RFTemp(
  data,
  oro,
  xlim = NULL,
  ylim = NULL,
  lapse = 6.5,
  lon_dim = "lon",
  lat_dim = "lat",
  time_dim = NULL,
  nolapse = FALSE,
  verbose = FALSE,
  compute_delta = FALSE,
  method = "bilinear",
  delta = NULL
)

Arguments

data

An object of the class 's2dv_cube' as returned by 'CST_Load', containing the temperature fields to downscale. The data object is expected to have an element named $data with at least two spatial dimensions named "lon" and "lat". (these default names can be changed with the lon_dim and lat_dim parameters).

oro

An object of the class 's2dv_cube' as returned by 'CST_Load', containing fine scale orography (in meters). The destination downscaling area must be contained in the orography field.

xlim

Vector with longitude bounds for downscaling; the full input field is downscaled if 'xlim' and 'ylim' are not specified.

ylim

Vector with latitude bounds for downscaling

lapse

Float with environmental lapse rate

lon_dim

String with name of longitude dimension

lat_dim

String with name of latitude dimension

time_dim

A vector of character string indicating the name of temporal dimension. By default, it is set to NULL and it considers "ftime", "sdate" and "time" as temporal dimensions.

nolapse

Logical, if true 'oro' is interpreted as a fine-scale climatology and used directly for bias correction.

verbose

Logical if to print diagnostic output.

compute_delta

Logical if true returns only a delta to be used for out-of-sample forecasts. Returns an object of the class 's2dv_cube', containing a delta. Activates 'nolapse = TRUE'.

method

String indicating the method used for interpolation: "nearest" (nearest neighbours followed by smoothing with a circular uniform weights kernel), "bilinear" (bilinear interpolation) The two methods provide similar results, but nearest is slightly better provided that the fine-scale grid is correctly centered as a subdivision of the large-scale grid.

delta

An object of the class 's2dv_cube', containing a delta to be applied to the downscaled input data. Activates 'nolapse = TRUE'. The grid of this object must coincide with that of the required output.

Value

CST_RFTemp() returns a downscaled CSTools object (i.e., of the class 's2dv_cube').

Author(s)

Jost von Hardenberg - ISAC-CNR, [e-mail]

References

Method described in ERA4CS MEDSCOPE milestone M3.2: High-quality climate prediction data available to WP4 here: https://www.medscope-project.eu/the-project/deliverables-reports/ and in H2020 ECOPOTENTIAL Deliverable No. 8.1: High resolution (1-10 km) climate, land use and ocean change scenarios available here: https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5b6cd2324&appId=PPGMS

Examples

# Generate simple synthetic data and downscale by factor 4
t <- rnorm(7 * 6 * 2 * 3 * 4)*10 + 273.15 + 10
dim(t) <- c(dataset = 1, member = 2, sdate = 3, ftime = 4, lat = 6, lon = 7)
lon <- seq(3, 9, 1)
lat <- seq(42, 47, 1)
coords <- list(lat = lat, lon = lon)
exp <- list(data = t, coords = coords)
attr(exp, 'class') <- 's2dv_cube'
o <- runif(29*29)*3000
dim(o) <- c(lats = 29, lons = 29)
lon <- seq(3, 10, 0.25)
lat <- seq(41, 48, 0.25)
coords <- list(lat = lat, lon = lon)
oro <- list(data = o, coords = coords)
attr(oro, 'class') <- 's2dv_cube'
res <- CST_RFTemp(data = exp, oro = oro, xlim = c(4,8), ylim = c(43, 46), 
                 lapse = 6.5, time_dim = 'ftime',
                 lon_dim = 'lon', lat_dim = 'lat')