| 5 | | In order to set a common framework with a precise definition of the variables, the `meteoR` package is based on the use of a vocabulary. In essence, the vocabulary is a table containing the standard names of a number of variables commonly used in impact studies and downscaling applications, subject to permanent revision or addition of new standard variables. The naming conventions and the units are based on the standard name [http://www.specs-fp7.eu/wiki/index.php/Data#SPECS_convention:_Standard_output_and_data_management_description table] provided in the frame of the SPECS project, although in case of conflict, and in order to maximize the inter-operability of the vocabulary, the nomenclature is also compliant with the [http://cf-pcmdi.llnl.gov/documents/cf-standard-names/standard-name-table/16/cf-standard-name-table.html/ NetCDF Climate and Forecast Metadata Convention]. |
| | 5 | In order to set a common framework with a precise definition of the variables, the `ecomsUDG.Raccess` package is based on the use of a vocabulary. In essence, the vocabulary is a table containing the standard names of a number of variables commonly used in impact studies and downscaling applications, subject to permanent revision or addition of new standard variables. The naming conventions and the units are based on the standard name [http://www.specs-fp7.eu/wiki/index.php/Data#SPECS_convention:_Standard_output_and_data_management_description table] provided in the frame of the SPECS project, although in case of conflict, and in order to maximize the inter-operability of the vocabulary, the nomenclature is also compliant with the [http://cf-pcmdi.llnl.gov/documents/cf-standard-names/standard-name-table/16/cf-standard-name-table.html/ NetCDF Climate and Forecast Metadata Convention]. |
| 13 | | "identifier","standard_name","units" |
| 14 | | "ta","temperature","degrees Celsius" |
| 15 | | "tas","2-meter temperature","degrees Celsius" |
| 16 | | "tasmax","maximum 2-m temperature","degrees Celsius" |
| 17 | | "tasmin","minimum 2-m temperature","degrees Celsius" |
| 18 | | "pr","Precipitation amount","mm" |
| 19 | | "zg","geopotential_height","m" |
| 20 | | "plev","air_pressure","Pa" |
| 21 | | "psl","air_pressure_at_sea_level","Pa" |
| 22 | | "ps","surface_air_pressure","Pa" |
| 23 | | "hus","specific_humidity","kg kg-1" |
| 24 | | "hur","relative_humidity","1" |
| 25 | | "ua","eastward_wind","m s-1" |
| 26 | | "va","northward_wind","m s-1" |
| | 14 | > library(ecomsUDG.Raccess) |
| | 15 | Loading required package: rJava |
| | 16 | Loading required package: sp |
| | 17 | > data(vocabulary) |
| | 18 | > print(vocabulary) |
| | 19 | identifier standard_name units |
| | 20 | 1 tas 2-meter temperature degrees Celsius |
| | 21 | 2 tasmax maximum 2-m temperature degrees Celsius |
| | 22 | 3 tasmin minimum 2-m temperature degrees Celsius |
| | 23 | 4 tp Total precipitation amount mm |
| | 24 | 5 psl air pressure at sea level Pa |
| 33 | | 1. On the one hand, the dictionary is intended for the translation of generic variables, as idiosyncratically defined in each particular dataset, to the standard variables defined in the vocabulary with their corresponding nomenclature and units. This is achieved by providing a correspondence between the name of the variable as encoded in the dataset (`short_name`) and the corresponding name of the standard variable as defined in the vocabulary (`identifier`), and by applying the corresponding transformation to the native variable in order to match the standard units by means of a `scale` factor and an `offset`. In some particular cases (e.g. the precipitation provided by the System4 model outputs), the variables are also deaccumulated. |
| | 32 | 1. On the one hand, the dictionary is intended for the translation of generic variables, as idiosyncratically defined in each particular dataset, to the standard variables defined in the vocabulary with their corresponding nomenclature and units. This is achieved by providing a correspondence between the name of the variable as encoded in the dataset (this is the variable name returned by the `datasetInventory` function) and the corresponding name of the standard variable as defined in the vocabulary (i.e., the `identifier`), and by applying the corresponding transformation to the native variable in order to match the standard units by means of an `offset` and a `scale` factor. In some particular cases (e.g. the precipitation provided by the System4 model outputs), the variables are also deaccumulated. |
| 36 | | The dictionary is a comma-sepparated text file (csv), that by default is identified with the same name than the dataset, and the extension ''.dic'', and stored in the same directory than the dataset, although its name and location can be other if adequately specified in the loading functions by the argument `dictionary`. The dictionary must be created ''"by hand"'' by the user, because it requires some ''a priori'' knowledge about the characteristics of the data stored in the dataset, that can be partly obtained using the function [wiki:../Functions#dataInventory dataInventory]. The columns of the dictionary are next described: |
| | 35 | In essence, the dictionary is a comma-sepparated text file (csv), that by default is identified with the same name than the argument `dataset` of the `loadSeasonalForecast` function. The dictionaries for the currently available datasets are included in the `ecomsUDG.Raccess` package, within the ''dictionaries'' folder. The dictionaries are read internally by `loadSeasonalForecast` to undertake the conversions needed for returning the standard variables, so by default, the user does not need to worry about it. In case an interested user wants to inspect a particular dictionary, he/she can proceed as follows: |
| | 36 | |
| | 37 | {{{ |
| | 38 | > ip <- installed.packages() |
| | 39 | > # Path to the installed library |
| | 40 | > libPath <- ip[grep("ecomsUDG.Raccess", ip[ ,1]), 2] |
| | 41 | > # Path to the dictionaries folder |
| | 42 | > dicPath <- paste(libPath, "/ecomsUDG.Raccess/dictionaries", sep = "") |
| | 43 | > list.files(dicPath) |
| | 44 | [1] "CFSv2_seasonal_16.csv" "System4_annual_15.csv" "System4_seasonal_15.csv" |
| | 45 | [4] "System4_seasonal_51.csv" |
| | 46 | > dic <- read.csv(list.files(dicPath, full = TRUE)[grep("CFSv2", list.files(dicPath))]) |
| | 47 | > str(dic.cfs) |
| | 48 | 'data.frame': 5 obs. of 9 variables: |
| | 49 | $ identifier : Factor w/ 5 levels "psl","tas","tasmax",..: 3 4 2 5 1 |
| | 50 | $ short_name : Factor w/ 5 levels "Maximum_temperature_height_above_ground" ... |
| | 51 | $ time_step : Factor w/ 1 level "6h": 1 1 1 1 1 |
| | 52 | $ lower_time_bound: int 0 0 0 0 0 |
| | 53 | $ upper_time_bound: int 6 6 6 6 0 |
| | 54 | $ aggr_fun : Factor w/ 5 levels "max","mean","min",..: 1 3 2 5 4 |
| | 55 | $ offset : num -273 -273 -273 0 0 |
| | 56 | $ scale : int 1 1 1 21600 1 |
| | 57 | $ deaccum : int 0 0 0 0 0 |
| | 58 | }}} |
| | 59 | |
| | 60 | The latest version of the dictionaries can be checked-out in the development version of the package at the [https://github.com/SantanderMetGroup/ecomsUDG.Raccess/tree/master/inst/dictionaries GitHub repository]. |
| | 61 | |
| | 62 | The columns of the dictionary are next described: |
| 48 | | In the following example, we show the characteristics of the dictionary constructed for the 15 members seasonal forecast of the ECMWF's System4 model: |
| 49 | | |
| 50 | | {{{ |
| 51 | | identifier,short_name,time_step,lower_time_bound,upper_time_bound,aggr_fun,offset,scale,deaccum |
| 52 | | tasmax,Maximum_temperature_at_2_metres_since_last_24_hours_surface,24h,0,24,max,-273.15,1,0 |
| 53 | | tasmin,Minimum_temperature_at_2_metres_since_last_24_hours_surface,24h,0,24,min,-273.15,1,0 |
| 54 | | tas,Mean_temperature_at_2_metres_since_last_24_hours_surface,24h,0,24,mean,-273.15,1,0 |
| 55 | | pr,Total_precipitation_surface,24h,0,24,sum,0,1000,1 |
| 56 | | psl,Mean_sea_level_pressure_surface,6h,0,0,none,0,1,0 |
| 57 | | }}} |
| 58 | | |
| 59 | | |
| 60 | | Note that column names matter (not so their relative order), because the data load functions will perform the conversion of the variables to the standard format by finding the corresponding values by the name of the columns. The [https://www.meteo.unican.es/trac/meteo/attachment/wiki/EcomsUdg/meteoR_v1_0.zip meteoR] package includes some dictionaries, and specific examples are given in the [wiki:../Examples Examples section] |
