The different nature of the different climate products, models and variables, and the idiosyncratic naming and storage conventions often applied by the various modelling centres, makes necessary a previous homogeneization across datasets in order to implement a truly user-friendly toolbox for data access. The meteor package achieves this aim by defining a common vocabulary to all climate datasets. The particular variables of each dataset are translated -and transformed if necessary- into the common vocabulary by means of a dictionary. Both features are next described.
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 ?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 ?NetCDF Climate and Forecast Metadata Convention.
"identifier","standard_name","units" "ta","temperature","degrees Celsius" "tas","2-meter temperature","degrees Celsius" "tasmax","maximum 2-m temperature","degrees Celsius" "tasmin","minimum 2-m temperature","degrees Celsius" "pr","Precipitation amount","mm" "zg","geopotential_height","m" "plev","air_pressure","Pa" "psl","air_pressure_at_sea_level","Pa" "ps","surface_air_pressure","Pa" "hus","specific_humidity","kg kg-1" "hur","relative_humidity","1" "ua","eastward_wind","m s-1" "va","northward_wind","m s-1"
The dictionary is a table whose aim is twofold:
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 dataInventory?. The columns of the dictionary are next described:
In the following example, we show the characteristics of the dictionary constructed for the 15 members seasonal forecast of the ECMWF's System4 model:
identifier,short_name,time_step,lower_time_bound,upper_time_bound,aggr_fun,offset,scale,deaccum tasmax,Maximum_temperature_at_2_metres_since_last_24_hours_surface,24h,0,24,max,-273.15,1,0 tasmin,Minimum_temperature_at_2_metres_since_last_24_hours_surface,24h,0,24,min,-273.15,1,0 tas,Mean_temperature_at_2_metres_since_last_24_hours_surface,24h,0,24,mean,-273.15,1,0 pr,Total_precipitation_surface,24h,0,24,sum,0,1000,1 psl,Mean_sea_level_pressure_surface,6h,0,0,none,0,1,0
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 ?meteoR package includes some dictionaries, and specific examples are given in the Examples section?