From 06b315dcd7d470867498f3e5f9e6c3880c4ee111 Mon Sep 17 00:00:00 2001 From: Eva Rifa Date: Fri, 27 Oct 2023 17:01:04 +0200 Subject: [PATCH 1/3] Add CST_Start in documentation and substitute it in vignettes --- R/AbsToProbs.R | 4 +- R/AccumulationExceedingThreshold.R | 4 +- R/PeriodAccumulation.R | 4 +- R/PeriodMax.R | 4 +- R/PeriodMean.R | 4 +- R/PeriodMin.R | 4 +- R/PeriodVariance.R | 4 +- R/QThreshold.R | 4 +- R/SelectPeriodOnData.R | 4 +- R/Threshold.R | 4 +- R/TotalSpellTimeExceedingThreshold.R | 4 +- R/TotalTimeExceedingThreshold.R | 4 +- R/WindPowerDensity.R | 2 +- man/CST_AbsToProbs.Rd | 4 +- man/CST_AccumulationExceedingThreshold.Rd | 4 +- man/CST_PeriodAccumulation.Rd | 4 +- man/CST_PeriodMax.Rd | 4 +- man/CST_PeriodMean.Rd | 4 +- man/CST_PeriodMin.Rd | 4 +- man/CST_PeriodVariance.Rd | 4 +- man/CST_QThreshold.Rd | 4 +- man/CST_SelectPeriodOnData.Rd | 4 +- man/CST_Threshold.Rd | 4 +- man/CST_TotalSpellTimeExceedingThreshold.Rd | 4 +- man/CST_TotalTimeExceedingThreshold.Rd | 4 +- man/CST_WindPowerDensity.Rd | 2 +- vignettes/AgriculturalIndicators.Rmd | 321 ++++++++++++------ vignettes/Figures/GDD_SEAS5_Corr_Y13-16-1.png | Bin 16049 -> 4847 bytes vignettes/Figures/GST_ERA5_Climatology-1.png | Bin 14335 -> 4549 bytes vignettes/Figures/HarvestR_Bias_2013-1.png | Bin 8941 -> 4149 bytes vignettes/Figures/SU35_ERA5_Y2016-1.png | Bin 8124 -> 4229 bytes .../Figures/SU35_Percentile_SEAS5_Y2016-1.png | Bin 9212 -> 4563 bytes vignettes/Figures/SU35_SEAS5_BC_Y2016-1.png | Bin 8836 -> 4694 bytes vignettes/Figures/SU35_SEAS5_Y2016-1.png | Bin 7520 -> 3440 bytes .../Figures/WSDI_SEAS5_FRPSS_Y13-16-1.png | Bin 8902 -> 4738 bytes 35 files changed, 270 insertions(+), 151 deletions(-) diff --git a/R/AbsToProbs.R b/R/AbsToProbs.R index 247ba38..db8891e 100644 --- a/R/AbsToProbs.R +++ b/R/AbsToProbs.R @@ -5,8 +5,8 @@ #'(start dates) are provided, the function will create the Cumulative #'Distribution Function excluding the corresponding initialization. #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start An optional parameter to define the initial date of the period #' to select from the data by providing a list of two elements: the initial #' date of the period and the initial month of the period. By default it is set diff --git a/R/AccumulationExceedingThreshold.R b/R/AccumulationExceedingThreshold.R index 0b312e9..feee031 100644 --- a/R/AccumulationExceedingThreshold.R +++ b/R/AccumulationExceedingThreshold.R @@ -12,8 +12,8 @@ #' temperatures and 10°C between April 1st and October 31st} #'} #' -#'@param data An 's2dv_cube' object as provided by function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param threshold If only one threshold is used, it can be an 's2dv_cube' #' object or a multidimensional array with named dimensions. It must be in the #' same units and with the common dimensions of the same length as parameter diff --git a/R/PeriodAccumulation.R b/R/PeriodAccumulation.R index 41c9b67..89a4d37 100644 --- a/R/PeriodAccumulation.R +++ b/R/PeriodAccumulation.R @@ -10,8 +10,8 @@ #' August 21st to October 21st} #'} #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start An optional parameter to defined the initial date of the period #' to select from the data by providing a list of two elements: the initial #' date of the period and the initial month of the period. By default it is set diff --git a/R/PeriodMax.R b/R/PeriodMax.R index d0004e0..8c56156 100644 --- a/R/PeriodMax.R +++ b/R/PeriodMax.R @@ -12,8 +12,8 @@ #' that prevails during the wettest month.} #'} #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start An optional parameter to defined the initial date of the period #' to select from the data by providing a list of two elements: the initial #' date of the period and the initial month of the period. By default it is set diff --git a/R/PeriodMean.R b/R/PeriodMean.R index 69ffc8c..9106927 100644 --- a/R/PeriodMean.R +++ b/R/PeriodMean.R @@ -10,8 +10,8 @@ #' maximum temperature from April 1st to May 31st} #'} #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start An optional parameter to defined the initial date of the period #' to select from the data by providing a list of two elements: the initial #' date of the period and the initial month of the period. By default it is set diff --git a/R/PeriodMin.R b/R/PeriodMin.R index afe5eb8..74547cc 100644 --- a/R/PeriodMin.R +++ b/R/PeriodMin.R @@ -12,8 +12,8 @@ #' that prevails during the driest month.} #'} #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start An optional parameter to defined the initial date of the period #' to select from the data by providing a list of two elements: the initial #' date of the period and the initial month of the period. By default it is set diff --git a/R/PeriodVariance.R b/R/PeriodVariance.R index 77bf68d..f95b8e4 100644 --- a/R/PeriodVariance.R +++ b/R/PeriodVariance.R @@ -16,8 +16,8 @@ #' and is expressed as a percentage} #'} #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start An optional parameter to defined the initial date of the period #' to select from the data by providing a list of two elements: the initial #' date of the period and the initial month of the period. By default it is set diff --git a/R/QThreshold.R b/R/QThreshold.R index 19cda3c..6bd8d83 100644 --- a/R/QThreshold.R +++ b/R/QThreshold.R @@ -22,8 +22,8 @@ #' the sample used must be especified in sdate_dim parameter.} #'} #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param threshold An 's2dv_cube' object as output of a 'CST_' function in the #' same units as parameter 'data' and with the common dimensions of the element #' 'data' of the same length. A single scalar is also possible. diff --git a/R/SelectPeriodOnData.R b/R/SelectPeriodOnData.R index bef70be..a4cc07c 100644 --- a/R/SelectPeriodOnData.R +++ b/R/SelectPeriodOnData.R @@ -2,8 +2,8 @@ #' #' Auxiliary function to subset data for a specific period. #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param start A parameter to defined the initial date of the period to select #' from the data by providing a list of two elements: the initial date of the #' period and the initial month of the period. diff --git a/R/Threshold.R b/R/Threshold.R index ee4fa38..314bc70 100644 --- a/R/Threshold.R +++ b/R/Threshold.R @@ -5,8 +5,8 @@ #'day (time). This function calculates the corresponding value of a percentile #'given a dataset. #' -#'@param data An 's2dv_cube' object as provided function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param threshold A single scalar or vector indicating the relative #' threshold(s). It must contain values between 0 and 1. #'@param start An optional parameter to defined the initial date of the period diff --git a/R/TotalSpellTimeExceedingThreshold.R b/R/TotalSpellTimeExceedingThreshold.R index 1bc1bb3..cd2676e 100644 --- a/R/TotalSpellTimeExceedingThreshold.R +++ b/R/TotalSpellTimeExceedingThreshold.R @@ -16,8 +16,8 @@ #'by using function \code{AbsToProbs}. See section @examples. #'@seealso [Threshold()] and [AbsToProbs()]. #' -#'@param data An 's2dv_cube' object as provided by function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param threshold If only one threshold is used, it can be an 's2dv_cube' #' object or a multidimensional array with named dimensions. It must be in the #' same units and with the common dimensions of the same length as parameter diff --git a/R/TotalTimeExceedingThreshold.R b/R/TotalTimeExceedingThreshold.R index 5c6bb62..fa57208 100644 --- a/R/TotalTimeExceedingThreshold.R +++ b/R/TotalTimeExceedingThreshold.R @@ -20,8 +20,8 @@ #' 32 between April 21st and June 21st} #'} #' -#'@param data An 's2dv_cube' object as provided by function \code{CST_Load} in -#' package CSTools. +#'@param data An 's2dv_cube' object as provided function \code{CST_Start} or +#' \code{CST_Load} in package CSTools. #'@param threshold If only one threshold is used, it can be an 's2dv_cube' #' object or a multidimensional array with named dimensions. It must be in the #' same units and with the common dimensions of the same length as parameter diff --git a/R/WindPowerDensity.R b/R/WindPowerDensity.R index 3dc835a..4a2e51e 100644 --- a/R/WindPowerDensity.R +++ b/R/WindPowerDensity.R @@ -7,7 +7,7 @@ #'it will give inaccurate results if used with period means. #' #'@param wind An 's2dv_cube' object with instantaneous wind speeds expressed in -#' m/s obtained from CST_Load or s2dv_cube functions from CSTools pacakge. +#' m/s obtained from CST_Start or s2dv_cube functions from CSTools pacakge. #'@param ro A scalar, or alternatively a multidimensional array with the same #' dimensions as wind, with the air density expressed in kg/m^3. By default it #' takes the value 1.225, the standard density of air at 15ºC and 1013.25 hPa. diff --git a/man/CST_AbsToProbs.Rd b/man/CST_AbsToProbs.Rd index ef8f42d..45a733d 100644 --- a/man/CST_AbsToProbs.Rd +++ b/man/CST_AbsToProbs.Rd @@ -15,8 +15,8 @@ CST_AbsToProbs( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{An optional parameter to define the initial date of the period to select from the data by providing a list of two elements: the initial diff --git a/man/CST_AccumulationExceedingThreshold.Rd b/man/CST_AccumulationExceedingThreshold.Rd index 2bdee76..0bea015 100644 --- a/man/CST_AccumulationExceedingThreshold.Rd +++ b/man/CST_AccumulationExceedingThreshold.Rd @@ -17,8 +17,8 @@ CST_AccumulationExceedingThreshold( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided by function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{threshold}{If only one threshold is used, it can be an 's2dv_cube' object or a multidimensional array with named dimensions. It must be in the diff --git a/man/CST_PeriodAccumulation.Rd b/man/CST_PeriodAccumulation.Rd index 2c8fb5a..0820a0d 100644 --- a/man/CST_PeriodAccumulation.Rd +++ b/man/CST_PeriodAccumulation.Rd @@ -14,8 +14,8 @@ CST_PeriodAccumulation( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial diff --git a/man/CST_PeriodMax.Rd b/man/CST_PeriodMax.Rd index 7b01d14..a372a1d 100644 --- a/man/CST_PeriodMax.Rd +++ b/man/CST_PeriodMax.Rd @@ -14,8 +14,8 @@ CST_PeriodMax( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial diff --git a/man/CST_PeriodMean.Rd b/man/CST_PeriodMean.Rd index ab42066..323adae 100644 --- a/man/CST_PeriodMean.Rd +++ b/man/CST_PeriodMean.Rd @@ -14,8 +14,8 @@ CST_PeriodMean( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial diff --git a/man/CST_PeriodMin.Rd b/man/CST_PeriodMin.Rd index 9395699..9d3833f 100644 --- a/man/CST_PeriodMin.Rd +++ b/man/CST_PeriodMin.Rd @@ -14,8 +14,8 @@ CST_PeriodMin( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial diff --git a/man/CST_PeriodVariance.Rd b/man/CST_PeriodVariance.Rd index e28bf95..b04b4ed 100644 --- a/man/CST_PeriodVariance.Rd +++ b/man/CST_PeriodVariance.Rd @@ -14,8 +14,8 @@ CST_PeriodVariance( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial diff --git a/man/CST_QThreshold.Rd b/man/CST_QThreshold.Rd index b168375..a07d130 100644 --- a/man/CST_QThreshold.Rd +++ b/man/CST_QThreshold.Rd @@ -16,8 +16,8 @@ CST_QThreshold( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{threshold}{An 's2dv_cube' object as output of a 'CST_' function in the same units as parameter 'data' and with the common dimensions of the element diff --git a/man/CST_SelectPeriodOnData.Rd b/man/CST_SelectPeriodOnData.Rd index 5f12633..5e4eff4 100644 --- a/man/CST_SelectPeriodOnData.Rd +++ b/man/CST_SelectPeriodOnData.Rd @@ -7,8 +7,8 @@ CST_SelectPeriodOnData(data, start, end, time_dim = "time", ncores = NULL) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{start}{A parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial date of the diff --git a/man/CST_Threshold.Rd b/man/CST_Threshold.Rd index 2b4ea2f..07571b5 100644 --- a/man/CST_Threshold.Rd +++ b/man/CST_Threshold.Rd @@ -17,8 +17,8 @@ CST_Threshold( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{threshold}{A single scalar or vector indicating the relative threshold(s). It must contain values between 0 and 1.} diff --git a/man/CST_TotalSpellTimeExceedingThreshold.Rd b/man/CST_TotalSpellTimeExceedingThreshold.Rd index 940478f..831bf2c 100644 --- a/man/CST_TotalSpellTimeExceedingThreshold.Rd +++ b/man/CST_TotalSpellTimeExceedingThreshold.Rd @@ -16,8 +16,8 @@ CST_TotalSpellTimeExceedingThreshold( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided by function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{threshold}{If only one threshold is used, it can be an 's2dv_cube' object or a multidimensional array with named dimensions. It must be in the diff --git a/man/CST_TotalTimeExceedingThreshold.Rd b/man/CST_TotalTimeExceedingThreshold.Rd index cd99163..db9a3d6 100644 --- a/man/CST_TotalTimeExceedingThreshold.Rd +++ b/man/CST_TotalTimeExceedingThreshold.Rd @@ -16,8 +16,8 @@ CST_TotalTimeExceedingThreshold( ) } \arguments{ -\item{data}{An 's2dv_cube' object as provided by function \code{CST_Load} in -package CSTools.} +\item{data}{An 's2dv_cube' object as provided function \code{CST_Start} or +\code{CST_Load} in package CSTools.} \item{threshold}{If only one threshold is used, it can be an 's2dv_cube' object or a multidimensional array with named dimensions. It must be in the diff --git a/man/CST_WindPowerDensity.Rd b/man/CST_WindPowerDensity.Rd index d37fd9d..ec82d8a 100644 --- a/man/CST_WindPowerDensity.Rd +++ b/man/CST_WindPowerDensity.Rd @@ -15,7 +15,7 @@ CST_WindPowerDensity( } \arguments{ \item{wind}{An 's2dv_cube' object with instantaneous wind speeds expressed in -m/s obtained from CST_Load or s2dv_cube functions from CSTools pacakge.} +m/s obtained from CST_Start or s2dv_cube functions from CSTools pacakge.} \item{ro}{A scalar, or alternatively a multidimensional array with the same dimensions as wind, with the air density expressed in kg/m^3. By default it diff --git a/vignettes/AgriculturalIndicators.Rmd b/vignettes/AgriculturalIndicators.Rmd index 3c9cf7d..46f7acd 100644 --- a/vignettes/AgriculturalIndicators.Rmd +++ b/vignettes/AgriculturalIndicators.Rmd @@ -65,40 +65,81 @@ The spatial domain covers part of Douro Valley of Northern Portugal lon=[352.25, With `grid` set to **r1440x721**, the SEAS5 forecast would be interpolated to the 0.25-degree ERA5 grid by using the **bicubic** method given in `method`. -``` -S5path_prlr <- list(path = '/esarchive/exp/ecmwf/system5c3s/$STORE_FREQ$_mean/$VAR_NAME$_s0-24h/$VAR_NAME$_$START_DATE$.nc') - -path_ERA5prlr_CDS <- list(path = '/esarchive/recon/ecmwf/era5/$STORE_FREQ$_mean/$VAR_NAME$_f1h-r1440x721cds/$VAR_NAME$_$YEAR$$MONTH$.nc') - +```r sdates <- paste0(2013:2016, '04', '01') -c(prlr_exp, prlr_obs) %<-% CST_Load(var = 'prlr', - exp = list(S5path_prlr), - obs = list(path_ERA5prlr_CDS), - sdates = sdates, - lonmax = 353, lonmin = 352.25, - latmax = 41.75, latmin = 41, - storefreq = 'daily', - leadtimemin = 1, leadtimemax = 214, - nmember = 3, output = "lonlat", - grid = "r1440x721", method = 'bicubic') +lat_min = 41 +lat_max = 41.75 +lon_min = 352.25 +lon_max = 353 + +S5path_prlr <- paste0("/esarchive/exp/ecmwf/system5c3s/daily_mean/$var$_s0-24h/$var$_$sdate$.nc") +prlr_exp <- CST_Start(dataset = S5path_prlr, + var = "prlr", + member = startR::indices(1:3), + sdate = sdates, + ftime = startR::indices(1:214), + lat = startR::values(list(lat_min, lat_max)), + lat_reorder = startR::Sort(decreasing = TRUE), + lon = startR::values(list(lon_min, lon_max)), + lon_reorder = startR::CircularSort(0, 360), + synonims = list(lon = c('lon', 'longitude'), + lat = c('lat', 'latitude'), + member = c('member', 'ensemble'), + ftime = c('ftime', 'time')), + transform = startR::CDORemapper, + transform_extra_cells = 2, + transform_params = list(grid = "r1440x721", + method = "bicubic"), + transform_vars = c('lat', 'lon'), + return_vars = list(lat = NULL, + lon = NULL, ftime = 'sdate'), + retrieve = TRUE) + +dates_exp <- prlr_exp$attrs$Dates + +path_ERA5prlr_CDS <- paste0("/esarchive/recon/ecmwf/era5/daily_mean/$var$_f1h-r1440x721cds/$var$_$date$.nc") +prlr_obs <- CST_Start(dataset = path_ERA5prlr_CDS, + var = "prlr", + date = unique(format(dates_exp, '%Y%m')), + ftime = startR::values(dates_exp), + ftime_across = 'date', + ftime_var = 'ftime', + merge_across_dims = TRUE, + split_multiselected_dims = TRUE, + lat = startR::values(list(lat_min, lat_max)), + lat_reorder = startR::Sort(decreasing = TRUE), + lon = startR::values(list(lon_min, lon_max)), + lon_reorder = startR::CircularSort(0, 360), + synonims = list(lon = c('lon', 'longitude'), + lat = c('lat', 'latitude'), + ftime = c('ftime', 'time')), + transform = startR::CDORemapper, + transform_extra_cells = 2, + transform_params = list(grid = "r1440x721", + method = "bicubic"), + transform_vars = c('lat', 'lon'), + return_vars = list(lon = NULL, + lat = NULL, + ftime = 'date'), + retrieve = TRUE) ``` The output contains data and metadata for the experiment and the observations. The elements `prlr_exp$data` and `prlr_obs$data` have dimensions: -``` +```r dim(prlr_exp$data) -#dataset member sdate ftime lat lon -# 1 3 4 214 4 4 +# dataset var member sdate ftime lat lon +# 1 1 3 4 214 4 4 dim(prlr_obs$data) -#dataset member sdate ftime lat lon -# 1 1 4 214 4 4 +# dataset var sdate ftime lat lon +# 1 1 4 214 4 4 ``` To compute **SprR** of forecast and observation, we can run: -``` +```r SprR_exp <- CST_PeriodAccumulation(prlr_exp, start = list(21, 4), end = list(21, 6)) SprR_obs <- CST_PeriodAccumulation(prlr_obs, start = list(21, 4), end = list(21, 6)) ``` @@ -109,41 +150,41 @@ As mentioned, these parameters are optional, the function will take the entire t The dimensions of SprR forecasts and observations are: -``` +```r dim(SprR_exp$data) -#dataset member sdate lat lon -# 1 3 4 4 4 +# dataset var member sdate lat lon +# 1 1 3 4 4 4 dim(SprR_obs$data) -#dataset member sdate lat lon -# 1 1 4 4 4 +# dataset var sdate lat lon +# 1 1 4 4 4 ``` The forecast SprR for the 1st member from 2013-2016 of the 1st grid point in mm are: -``` -SprR_exp$data[1, 1, , 1, 1] * 86400 * 1000 -#[1] 93.23205 230.41904 194.01412 226.52614 +```r +SprR_exp$data[1, 1, 1, , 1, 1] * 86400 * 1000 +# [1] 93.23236 230.41754 194.01401 226.52564 ``` Dry springs will delay vegetative growth and reduce vigour and leaf area total surface. Fungal disease pressure will be lower and therefore there will be less need for protective and / or curative treatments, translating as less costs. Wet springs will promote higher vigour, increase the risk of fungal disease and disrupt vineyard operations as it may prevent machinery from getting in the vineyard due to mud. They are usually associated with higher costs. On the other hand, another moisture-related indicators, **HarvestR**, can be computed by using `PeriodAccumulation` as well, with the defined period as the following lines. -``` +```r HarvestR_exp <- CST_PeriodAccumulation(prlr_exp, start = list(21, 8), end = list(21, 10)) HarvestR_obs <- CST_PeriodAccumulation(prlr_obs, start = list(21, 8), end = list(21, 10)) ``` The forecast HarvestR for the 1st member from 2013-2016 of the 1st grid point in mm are: -``` -HarvestR_exp$data[1, 1, , 1, 1] * 86400 * 1000 -#[1] 52.30026 42.88068 156.87961 32.18579 +```r +HarvestR_exp$data[1, 1, 1, , 1, 1] * 86400 * 1000 +# [1] 52.30058 42.88070 156.87922 32.18567 ``` To compute the 2013-2016 ensemble-mean bias of forecast HarvestR, run -``` +```r fcst <- drop(HarvestR_exp$data) * 86400 * 1000 obs <- drop(HarvestR_obs$data) * 86400 * 1000 @@ -152,7 +193,7 @@ Bias <- MeanDims((fcst - InsertDim(obs, 1, dim(fcst)['member'])), 'member') To plot the map of ensemble-mean bias of HarvestR forecast, run -``` +```r cols <- c('#b2182b', '#d6604d', '#f4a582', '#fddbc7', '#d1e5f0', '#92c5de', '#4393c3', '#2166ac') @@ -178,42 +219,81 @@ For the function `PeriodMean`, we use Growing Season Temperature (**GST**) as an Firstly, we prepare a sample data of daily mean temperature of SEAS5 and ERA5 data sets with the same starting dates, spatial domain, interpolation grid and method by running -``` -S5path <- list(path = '/esarchive/exp/ecmwf/system5c3s/$STORE_FREQ$_mean/$VAR_NAME$_f6h/$VAR_NAME$_$YEAR$$MONTH$01.nc') -ERA5path <- list(path = '/esarchive/recon/ecmwf/era5/$STORE_FREQ$_mean/$VAR_NAME$_f1h-r1440x721cds/$VAR_NAME$_$YEAR$$MONTH$.nc') - -c(tas_exp, tas_obs) %<-% CST_Load(var = 'tas', exp = list(S5path), obs = list(ERA5path), - sdates = sdates, lonmax = 353, lonmin = 352.25, - latmax = 41.75, latmin = 41, - storefreq = 'daily', - leadtimemin = 1, leadtimemax = 214, - nmember = 3, output = "lonlat", - grid = "r1440x721", method = 'bicubic') +```r +S5path <- paste0("/esarchive/exp/ecmwf/system5c3s/daily_mean/$var$_f6h/$var$_$sdate$.nc") +tas_exp <- CST_Start(dataset = S5path, + var = "tas", + member = startR::indices(1:3), + sdate = sdates, + ftime = startR::indices(1:214), + lat = startR::values(list(lat_min, lat_max)), + lat_reorder = startR::Sort(decreasing = TRUE), + lon = startR::values(list(lon_min, lon_max)), + lon_reorder = startR::CircularSort(0, 360), + synonims = list(lon = c('lon', 'longitude'), + lat = c('lat', 'latitude'), + member = c('member', 'ensemble'), + ftime = c('ftime', 'time')), + transform = startR::CDORemapper, + transform_extra_cells = 2, + transform_params = list(grid = "r1440x721", + method = "bicubic"), + transform_vars = c('lat', 'lon'), + return_vars = list(lat = NULL, + lon = NULL, ftime = 'sdate'), + retrieve = TRUE) +dates_exp <- tas_exp$attrs$Dates + +ERA5path <- paste0("/esarchive/recon/ecmwf/era5/daily_mean/$var$_f1h-r1440x721cds/$var$_$date$.nc") +tas_obs <- CST_Start(dataset = ERA5path, + var = "tas", + date = unique(format(dates_exp, '%Y%m')), + ftime = startR::values(dates_exp), + ftime_across = 'date', + ftime_var = 'ftime', + merge_across_dims = TRUE, + split_multiselected_dims = TRUE, + lat = startR::values(list(lat_min, lat_max)), + lat_reorder = startR::Sort(decreasing = TRUE), + lon = startR::values(list(lon_min, lon_max)), + lon_reorder = startR::CircularSort(0, 360), + synonims = list(lon = c('lon', 'longitude'), + lat = c('lat', 'latitude'), + ftime = c('ftime', 'time')), + transform = startR::CDORemapper, + transform_extra_cells = 2, + transform_params = list(grid = "r1440x721", + method = "bicubic"), + transform_vars = c('lat', 'lon'), + return_vars = list(lon = NULL, + lat = NULL, + ftime = 'date'), + retrieve = TRUE) ``` The output contains observations `tas_dv$obs$data` and forecast `tas_dv$exp$data`, and their dimensions and summaries are like -``` +```r dim(tas_obs$data) -#dataset member sdate ftime lat lon -# 1 1 4 214 4 4 +# dataset var sdate ftime lat lon +# 1 1 4 214 4 4 dim(tas_exp$data) -#dataset member sdate ftime lat lon -# 1 3 4 214 4 4 +# dataset var member sdate ftime lat lon +# 1 1 3 4 214 4 4 summary(tas_obs$data - 273.15) # Min. 1st Qu. Median Mean 3rd Qu. Max. -# 3.63 13.97 17.25 17.29 20.75 30.21 +# 3.627 13.974 17.248 17.294 20.752 30.206 summary(tas_exp$data - 273.15) -# Min. 1st Qu. Median Mean 3rd Qu. Max. -# 0.54 11.65 16.56 16.50 21.25 31.41 +# Min. 1st Qu. Median Mean 3rd Qu. Max. +# 0.5363 11.6517 16.5610 16.4961 21.2531 31.4063 ``` To compute the GST for both observation and forecast, run the following lines -``` +```r # change the unit of temperature from °C to K tas_exp$data <- tas_exp$data - 273.15 @@ -230,7 +310,7 @@ Since the period considered for GST is the entire period for starting month of A The summaries and dimensions of the output are as follows: -``` +```r summary(GST_exp$data) # Min. 1st Qu. Median Mean 3rd Qu. Max. # 14.23 15.78 16.50 16.50 17.17 18.70 @@ -240,17 +320,17 @@ summary(GST_obs$data) # 15.34 16.77 17.22 17.29 18.00 18.75 dim(GST_exp$data) -#dataset member sdate lat lon -# 1 3 4 4 4 +# dataset var member sdate lat lon +# 1 1 3 4 4 4 dim(GST_obs$data) -#dataset member sdate lat lon -# 1 1 4 4 4 +# dataset var sdate lat lon +# 1 1 4 4 4 ``` Here, we plot the 2013-2016 mean climatology of ERA5 GST by running -``` +```r # compute ERA5 GST climatology GST_Clim <- MeanDims(drop(GST_obs$data), 'sdate') @@ -288,29 +368,68 @@ Here, we take SU35 as example, therefore the daily temperature maximum of the en Load SEAS5 and ERA5 daily temperature maximum by running -``` -S5path <- list(path = '/esarchive/exp/ecmwf/system5c3s/$STORE_FREQ$/$VAR_NAME$/$VAR_NAME$_$YEAR$$MONTH$01.nc') -ERA5path <- list(path = '/esarchive/recon/ecmwf/era5/$STORE_FREQ$/$VAR_NAME$-r1440x721cds/$VAR_NAME$_$YEAR$$MONTH$.nc') - -c(tasmax_exp, tasmax_obs) %<-% CST_Load(var = 'tasmax', exp = list(S5path), - obs = list(ERA5path), sdates = sdates, - lonmax = 353, lonmin = 352.25, - latmax = 41.75, latmin = 41, storefreq = 'daily', - leadtimemin = 1, leadtimemax = 214, nmember = 3, - output = "lonlat", grid = "r1440x721", - method = 'bicubic', nprocs = 1) +```r +S5path <- paste0("/esarchive/exp/ecmwf/system5c3s/daily/$var$/$var$_$sdate$.nc") +tasmax_exp <- CST_Start(dataset = S5path, + var = "tasmax", + member = startR::indices(1:3), + sdate = sdates, + ftime = startR::indices(1:214), + lat = startR::values(list(lat_min, lat_max)), + lat_reorder = startR::Sort(decreasing = TRUE), + lon = startR::values(list(lon_min, lon_max)), + lon_reorder = startR::CircularSort(0, 360), + synonims = list(lon = c('lon', 'longitude'), + lat = c('lat', 'latitude'), + member = c('member', 'ensemble'), + ftime = c('ftime', 'time')), + transform = startR::CDORemapper, + transform_extra_cells = 2, + transform_params = list(grid = "r1440x721", + method = "bicubic"), + transform_vars = c('lat', 'lon'), + return_vars = list(lat = NULL, + lon = NULL, ftime = 'sdate'), + retrieve = TRUE) +dates_exp <- tasmax_exp$attrs$Dates + +ERA5path <- paste0("/esarchive/recon/ecmwf/era5/daily/$var$-r1440x721cds/$var$_$date$.nc") +tasmax_obs <- CST_Start(dataset = ERA5path, + var = "tasmax", + date = unique(format(dates_exp, '%Y%m')), + ftime = startR::values(dates_exp), + ftime_across = 'date', + ftime_var = 'ftime', + merge_across_dims = TRUE, + split_multiselected_dims = TRUE, + lat = startR::values(list(lat_min, lat_max)), + lat_reorder = startR::Sort(decreasing = TRUE), + lon = startR::values(list(lon_min, lon_max)), + lon_reorder = startR::CircularSort(0, 360), + synonims = list(lon = c('lon', 'longitude'), + lat = c('lat', 'latitude'), + ftime = c('ftime', 'time')), + transform = startR::CDORemapper, + transform_extra_cells = 2, + transform_params = list(grid = "r1440x721", + method = "bicubic"), + transform_vars = c('lat', 'lon'), + return_vars = list(lon = NULL, + lat = NULL, + ftime = 'date'), + retrieve = TRUE) ``` Check the unit of temperature to from °C to K for the comparison with the threshold defined (for example 35°C here). -``` +```r tasmax_exp$data <- tasmax_exp$data - 273.15 tasmax_obs$data <- tasmax_obs$data - 273.15 ``` Computing SU35 for forecast and observation by running -``` +```r threshold <- 35 SU35_exp <- CST_TotalTimeExceedingThreshold(tasmax_exp, threshold = threshold, start = list(1, 4), end = list(31, 10)) @@ -320,40 +439,40 @@ SU35_obs <- CST_TotalTimeExceedingThreshold(tasmax_obs, threshold = threshold, The summaries of SU35 forecasts and observations are given below. -``` +```r summary(SU35_exp$data) # Min. 1st Qu. Median Mean 3rd Qu. Max. -# 0.00 2.00 5.00 7.12 12.00 26.00 +# 0.000 2.000 5.000 7.135 12.000 26.000 summary(SU35_obs$data) # Min. 1st Qu. Median Mean 3rd Qu. Max. -# 0.000 0.000 1.000 2.609 5.000 10.000 +# 0.000 0.000 1.000 2.609 5.000 10.000 ``` As shown in the summaries, SEAS5 SU35 forecasts are overestimated by 5 days in terms of mean value. Therefore, `CST_BiasCorrection` is used to bias adjust the SU35 forecasts. -``` +```r res <- CST_BiasCorrection(obs = SU35_obs, exp = SU35_exp) SU35_exp_BC <- drop(res$data) summary(SU35_exp_BC) # Min. 1st Qu. Median Mean 3rd Qu. Max. -# -1.419 0.000 1.613 2.831 4.756 17.768 +# -1.523 0.000 1.613 2.830 4.756 17.768 ``` Since there are negative values after bias adjustment, all negative data is converted to zero. -``` +```r SU35_exp_BC[SU35_exp_BC < 0] <- 0 summary(SU35_exp_BC) # Min. 1st Qu. Median Mean 3rd Qu. Max. -# 0.000 0.000 1.613 2.943 4.756 17.768 +# 0.000 0.000 1.613 2.941 4.756 17.768 ``` Plot the bias-adjusted SU35 forecast in 2016 by running -``` +```r SU35_obs_Y2016 <- drop(SU35_obs$data)[4, , ] SU35_exp_Y2016 <- MeanDims(drop(SU35_exp$data)[, 4, , ], 'member') SU35_exp_BC_Y2016 <- MeanDims(SU35_exp_BC[, 4, , ], 'member') @@ -414,34 +533,34 @@ The revised definition of SU35 is to reduce the potential influence induced by t As mentioned, the forecast is translated to its percentile by using the function `ABsToProbs` by running -``` +```r exp_percentile <- AbsToProbs(tasmax_exp$data) S5txP <- aperm(drop(exp_percentile), c(2, 1, 3, 4, 5)) ``` After that, based on 35 of threshold, the percentile corresponding to each observational value can be calculated as follows. -``` +```r obs_percentile <- QThreshold(tasmax_obs$data, threshold = 35) obs_percentile <- drop(obs_percentile) ``` After translating both forecasts and observations into probabilities, the comparison can then be done by running -``` +```r SU35_exp_Percentile <- TotalTimeExceedingThreshold(S5txP, threshold = obs_percentile, time_dim = 'ftime') ``` Compute the same ensemble-mean SU35 **with percentile adjustment** in 2016 by running -``` +```r SU35_exp_per_Y2016 <- MeanDims(SU35_exp_Percentile[4, , , ], 'member') ``` Plot the same map for comparison -``` +```r toptitle <- 'SU35 forecast with percentile adjustment in 2016' PlotEquiMap(SU35_exp_per_Y2016, lon = tasmax_obs$coords$lon, lat = tasmax_obs$coords$lat, @@ -468,14 +587,14 @@ The definition of GDD is the summation of daily differences between daily averag *Note: The data is in degrees Celsiusi at this point* -``` +```r GDD_exp <- CST_AccumulationExceedingThreshold(tas_exp, threshold = 10, diff = TRUE) GDD_obs <- CST_AccumulationExceedingThreshold(tas_obs, threshold = 10, diff = TRUE) ``` The summaries of GDD are -``` +```r summary(GDD_exp$data) # Min. 1st Qu. Median Mean 3rd Qu. Max. # 1021 1331 1480 1469 1596 1873 @@ -487,7 +606,7 @@ summary(GDD_obs$data) To compute the correlation coefficient for the period from 2013-2016, run the following lines -``` +```r # reorder the dimension fcst <- Reorder(drop(GDD_exp$data), c(4, 3, 2, 1)) obs <- Reorder(drop(GDD_obs$data), c(3, 2, 1)) @@ -498,7 +617,7 @@ GDD_Corr <- Reorder(EnsCorr, c(2, 1)) To plot the map of correlation coefficient of GDD for the 2013-2016 period. -``` +```r cols <- c("#f7fcf5", "#e5f5e0", "#c7e9c0", "#a1d99b", "#74c476") toptitle <- '2013-2016 correlation coefficient of GDD' PlotEquiMap(GDD_Corr, lon = tas_obs$coords$lon, lat = tas_obs$coords$lat, @@ -522,32 +641,32 @@ One of the critical agricultural indicators related to dry spell is the **Warm S The maximum temperature data used in Section 3. Since the daily maximum temperature needs to compare to its 90th percentile, the function `Threshold` in the `CSIndicators` package is required to compute the percentile of observations used for each day. Here the same period (2013-2016) is considered. -``` -tx_p <- CST_Threshold(tasmax_obs, threshold = 0.9) +```r +tx_p <- CST_Threshold(tasmax_obs, threshold = 0.9, memb_dim = NULL) ``` The output will be the 90th percentile of each day of each grid point derived by using all the years in the data.See the dimension and summary as below. -``` +```r dim(tx_p$data) -#dataset ftime lat lon -# 1 214 4 4 +# dataset var ftime lat lon +# 1 1 214 4 4 summary(tx_p$data) -# Min. 1st Qu. Median Mean 3rd Qu. Max. +# Min. 1st Qu. Median Mean 3rd Qu. Max. # 13.83 22.08 26.08 26.22 30.72 36.72 ``` With the prepared threshold (90th percentile), the WSDI can be computed by running -``` +```r WSDI_exp <- CST_TotalSpellTimeExceedingThreshold(tasmax_exp, threshold = tx_p, spell = 6) WSDI_obs <- CST_TotalSpellTimeExceedingThreshold(tasmax_obs, threshold = tx_p, spell = 6) ``` After checking the summaries, compute the Fair Ranked Probability Skill Score (FRPSS) of WSDI by running the following lines -``` +```r # Reorder the data fcst <- Reorder(drop(WSDI_exp$data), c(4, 3, 2, 1)) obs <- Reorder(drop(WSDI_obs$data), c(3, 2, 1)) @@ -559,7 +678,7 @@ summary(fcst) summary(obs) # Min. 1st Qu. Median Mean 3rd Qu. 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%\VignetteEngine{knitr::knitr} @@ -58,7 +60,7 @@ library(s2dv) To obtain the precipitation forecast and observation, we load the daily precipitation (**prlr** given in `var`) data sets of ECMWF SEAS5 seasonal forecast and ERA5 reanalysis for the four starting dates 20130401-20160401 (provided in `sdates`) with the entire 7-month forecast time, April-October (214 days in total given in parameter `leadtimemax`). -The pathways of SEAS5 and ERA5 are given in the lists with some **whitecards (inside two dollar signs)** used to replace the variable name and iterative items such as year and month. See details of requirements in Section 4 in vignette [Data retrieval and storage](https://cran.r-project.org/package=CSTools/vignettes/Data_Considerations.html) from CSTools package. +The pathways of SEAS5 and ERA5 are given in the lists with some **whitecards (inside two dollar signs)** used to replace the variable name and iterative items such as year and month. See details of requirements in Section 5 in vignette [Data retrieval and storage](https://cran.r-project.org/package=CSTools/vignettes/Data_Considerations.html) from CSTools package. The spatial domain covers part of Douro Valley of Northern Portugal lon=[352.25, 353], lat=[41, 41.75]. These four values are provided in `lonmin`, `lonmax`, `latmin` and `latmax`. @@ -271,7 +273,7 @@ tas_obs <- CST_Start(dataset = ERA5path, retrieve = TRUE) ``` -The output contains observations `tas_dv$obs$data` and forecast `tas_dv$exp$data`, and their dimensions and summaries are like +The output contains observations `tas_obs$data` and forecast `tas_exp$data`, and their dimensions and summaries are like ```r dim(tas_obs$data) -- GitLab From 19ccbb25dc8ec8285978feafdb0a495a8038d27d Mon Sep 17 00:00:00 2001 From: Eva Rifa Date: Tue, 31 Oct 2023 12:13:59 +0100 Subject: [PATCH 3/3] Return to original figures because the results are equal --- vignettes/Figures/GDD_SEAS5_Corr_Y13-16-1.png | Bin 4847 -> 16049 bytes vignettes/Figures/GST_ERA5_Climatology-1.png | Bin 4549 -> 14335 bytes vignettes/Figures/HarvestR_Bias_2013-1.png | Bin 4149 -> 8941 bytes vignettes/Figures/SU35_ERA5_Y2016-1.png | Bin 4229 -> 8124 bytes .../Figures/SU35_Percentile_SEAS5_Y2016-1.png | Bin 4563 -> 9212 bytes 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