# Temperature downscaling of a CSTools object using lapse rate correction or a reference field 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. ```r 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. ## Returns CST_RFTemp() returns a downscaled CSTools object (i.e., of the class 's2dv_cube'). ## Examples ```r # 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') ``` ## 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/](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](https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5b6cd2324&appId=PPGMS) ## Author(s) Jost von Hardenberg - ISAC-CNR, j.vonhardenberg@isac.cnr.it

CST_RFTemp function