Version 40 (modified by juaco, 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 internal 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. 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)
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, but is not currently available in ECOMS-UDG; P indicates that the variable exists in the original dataset and work is in progress to incorporate it to the ECOMS-UDG; 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 are 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: | ||||||||
short name | Variable description | System4 seasonal_15 | System4 seasonal_51 | System4 annual_15 | CFSv2 seasonal_16 | SPECS-ESGF | ||
tas | Near-Surface air temperature | 6h | DM | DM | e | |||
tasmax | Daily Maximum Near-Surface Air Temperature | DX | DX | DX | DX | e | ||
tasmin | Daily Minimum Near-Surface Air Temperature | DN | DN | DN | DN | e | ||
tp | Total precipitation amount | DAr | DAr | DAr | DA | e | ||
psl | Sea Level Pressure | 6h | 6h | e | e | e | ||
ps | Surface air pressure | P(*) | e | |||||
wsp | Wind speed (at 10m) | P(*) | e | e | e | |||
tdps | 2m Dewpoint Temperature | 6h | e | e | ||||
huss | Surface (2m) specific humidity | P(*) | e | |||||
rsds | Surface Downwelling Shortwave Radiation | DA | e | e | e | |||
rlds | Net Longwave Surface Radiation | DA | e | e | e | |||
sst | Sea surface temperature | e | e | e | ||||
uas | Eastward Near-Surface Wind | 6h | e | e | e | e | ||
vas | Northward Near-Surface Wind | 6h | e | e | e | e | ||
wspmax | Wind speed (at 10m) | e | e | e | e | |||
wgust | Wind gust | e | e | |||||
mrso | Total Soil Moisture Content | e | e | |||||
mrros | Surface runoff flux | e | e | e | ||||
mrro | Total Runoff | e | e | e | ||||
ssro | Sub-surface runoff rate | e | e | |||||
prsn | Snowfall Flux | e | e | e | ||||
wcsl | Water Content of Soil Layer | e | e | |||||
zg700 | Geopotential 700mb | 12h | e | e | e | |||
zg850 | Geopotential 850mb | e | e | e | e | |||
zg925 | Geopotential 925mb | e | e | |||||
zg1000 | Geopotential 1000mb | 12h | e | e | ||||
ua850 | Eastward Wind | 12h | e | e | e | |||
va850 | Northward Wind | 12h | e | e | e | |||
ua925 | Eastward Wind | 12h | e | e | ||||
va925 | Northward Wind | 12h | e | e | ||||
z700 | Geopotential Height | P(*) | e | e | e | |||
z1000 | Geopotential Height | P(*) | e | e | ||||
sd | Snow Depth | 24h | e | e | ||||
zsfc | Orography | 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?.