Changes between Version 8 and Version 9 of udg/ecoms/dataserver/interfaces/python
- Timestamp:
- Apr 19, 2013 11:34:20 AM (9 years ago)
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udg/ecoms/dataserver/interfaces/python
v8 v9 14 14 * `var`: Variable code. Argument values currently accepted are `tas`, `tasmin`, `tasmax`, `pr` or `mslp`, as internally defined in the vocabulary for System4 following the nomenclature displayed in the table below. However, note that new variables and datasets will be progressively included. Note that depending on the time step of the variable the units might be referred to different time aggregations. For instance, currently `mslp` is 6-hourly, and thus the 6-hourly mean value is returned for each time step. Similarly, 24-h accumulated values are returned for `pr`, and so on. Note that the ''instantaneous'' and ''aggregated'' fields in table below refer to the potential time step values that the variables may take, which does not mean that the resolution provided by the System4 model is necessarily that. 15 15 16 ||='''Short Name'''=||='''Long name'''=||='''Units'''=||='''Instantaneous'''=||='''Aggregated'''=||17 || tasmax || Maximum temperature at 2 metres || K || No || Yes ||18 || tasmin || Minimum temperature at 2 metres || K || No || Yes ||19 || tas || Mean temperature at 2 metres || K || Yes || Yes ||20 || pr || Total precipitation accumulated || mm || No || Yes ||21 || mslp || Mean sea level pressure || Pa || Yes || Yes ||16 ||='''Short Name'''=||='''Long name'''=||='''Units'''=||='''Instantaneous'''=||='''Aggregated'''=|| 17 || tasmax || Maximum temperature at 2 metres || K || No || Yes || 18 || tasmin || Minimum temperature at 2 metres || K || No || Yes || 19 || tas || Mean temperature at 2 metres || K || Yes || Yes || 20 || pr || Total precipitation accumulated || mm || No || Yes || 21 || mslp || Mean sea level pressure || Pa || Yes || Yes || 22 22 23 23 * `members`: List of members to select. In the above case, a single member (the first) of the System4 ensemble is loaded, but additional members could be also specified (e.g. `members=[0,1,2,3,4]` for the first five members). … … 60 60 >>> plot_map(temporal_mean,ud,season,var) 61 61 }}} 62
