WikiPrint - from Polar Technologies

The ?ECOMS UDG provides access to a reduced number of variables for the available datasets?. The following list of variables has been identified (and is periodically updated) according to the user's needs, receiving feedback from EUPORIAS WP22 (climate information indices, CIIs), WP23 (impact models), WP21 (calibration and downscaling) and SPECS WP61 (pilot applications) and WP52 (calibration and downscaling). See the section on the assessment of user's needs for more details.

Note that the R names below correspond to the vocabulary names used in the R data access package, which may not correspond to the different vocabularies of each particular dataset. These names have been used for homogenization purposes to build the vocabulary? of the R package for data access. Note that, data homogenization and aggregation is only provided through the R data access package.

In order to specify the particular temporal frequency/aggregation available for the variables in the different datasets, the following codes are used in the table below: 6h (6-hourly instantaneous data). 12h (12-hourly instantaneous data). 24h (24-hourly instantaneous data). DM (daily mean value). DX (daily maximum value). DN (daily minimum value). DA (daily accumulated data). DAr (accumulated since the initialization time ?runtime). fx (static field)

In the table below, boldface codes (e.g. 6h) indicate variables already available through the ECOMS UDG. Italics are used for work in progress (variables to be included in the next update). e indicates that a variable exists in the original dataset but it is not planned to be included yet; blanks indicate that the variables do not exist in the original dataset. Codes ended by (*) indicate variables which do NOT exist in the corresponding dataset, but will be derived/approximated from other available variables through the R data access package. More information on the particular approximations used are given in the ?variables-datasets mapping.

Availability for the following datasets:
R name Variable description ?System4 seasonal_15 ?System4 seasonal_51 ?System4 annual_15 ?CFSv2 seasonal_16 ?SPECS-ESGF
tasNear-Surface air temperature 6h DM DM e
tasmaxDaily Maximum Near-Surface Air Temperature DX DX DX DX e
tasminDaily Minimum Near-Surface Air Temperature DN DN DN DN e
tpTotal precipitation amount DAr DAr DAr DA e
pslSea Level Pressure 6h 6h e e e
psSurface air pressure 6h(*) e
wspWind speed (at 10m) 6h(*) e e e
tdps2m Dewpoint Temperature 6h e e
hussSurface (2m) specific humidity 6h(*) e
rsdsSurface Downwelling Shortwave Radiation DA e e e
rldsNet Longwave Surface Radiation DA e e e
sstSea surface temperature e e e
uasEastward Near-Surface Wind 6h e e e e
vasNorthward Near-Surface Wind 6h e e e e
wspmaxWind speed (at 10m) e e e e
wgustWind gust e e
mrsoTotal Soil Moisture Content e e
mrrosSurface runoff flux e e e
mrroTotal Runoff e e e
ssroSub-surface runoff rate e e
prsnSnowfall Flux e e e
wcslWater Content of Soil Layer e e
sdSnow Depth 24h e e
3D vars @ isobaric surface levels
uaEastward Wind 12h @ 925,850 mb e e e
vaNorthward Wind 12h @ 925,850 mb e e e
zGeopotential heigth 12h @ 1000,700 mb e e e
Static fields
zsfcOrography fx e e

Data Homogeneization: The different nature of the datasets, and the idiosyncratic naming and storage conventions often applied by the modelling centres, makes necessary an homogeneization across datasets in order to implement a truly user-friendly toolbox for data access. To this aim, the R package for data access has been developed. Data homogeneization is achieved through the creation of a common vocabulary. The particular variables of each dataset are then translated -and transformed if necessary- into the common vocabulary by means of a dictionary. Both features -vocabulary and dictionary- are described here?.