Version 39 (modified by maru, 7 years ago) (diff)


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 short names below are standard codes which may not correspond to the naming conventions of the different datasets (boldface indicates standard variables according to the NetCDF Climate and Forecast Metadata Convention and to the naming convention within SPECS). These short names have been used for homogenization purposes to build the vocabulary? of the R package for data access.

Temporal frequency/aggregation Codes: 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)

The variables available and ready to use through the ECOMS UDG are indicated using boldface codes. e indicates that variable exists in the original dataset; P indicates that the variable exists in the original dataset and work is in progress to incorporate it to the UDG; blanks indicate lack of data.

Availability for the following datasets:
short 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 6h e
psSurface air pressure P(*) e
wspWind speed (at 10m) P(*) e e e
tdps2m Dewpoint Temperature 6h e e
hussSurface (2m) specific humidity P(*) 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
zg700Geopotential 700mb 12h e e e
zg850Geopotential 850mb e e e e
zg925Geopotential 925mb e e
zg1000Geopotential 1000mb 12h e e
ua850Eastward Wind 12h e e e
va850Northward Wind 12h e e e
ua925Eastward Wind 12h e e
va925Northward Wind 12h e e
z700Geopotential Height P(*) e e e
z1000Geopotential Height P(*) e e
sdSnow Depth 24h e e
zsfcOrography fx e e

(*) These variables do NOT exist in the corresponding dataset, but they will be derived/approximated from other available variables through the R package for data access. More information in the table of variables-datasets mapping.

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?.