served from 129.236.110.25
max mean mean ∂time ∂lon [ UY precipitacion ] : ∂time ∂lon Precipitacion data
precipitacion partial_lon partial_lon partial_lon partial_time partial_time partial_time partial_time partial_time ∂time ∂lon Precipitacion from UY: PRECM_UY_v1p1: Gridded precipitation dataset at 30 km. It corresponds to Experiment No. 3 in the documentation. isIndependent Variables (Grids)
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- units
- 8.25059224988386 meter radian-1 east year-2
- history
- mean mean $partialdiff sub time$ $partialdiff sub lon$ [ UY precipitacion ]
- Averaged over lat[36S, 29.5S] minimum 0.0% data present
Averaged over lon[58.85526W, 53.64474W] minimum 0.0% data present
max mean mean $partialdiff sub time$ $partialdiff sub lon$ [ UY precipitacion ]- max over time[16 Feb 1925 - 15 Mar 1925, 16 Oct 2009 - 15 Nov 2009]
- Averaged over lat[36S, 29.5S] minimum 0.0% data present
References
Muñoz, ?~A.G., González, P., Baethgen, W.,: Gridded precipitation dataset ff or Uruguay. Version 1.1Last updated: Sun, 02 Jun 2024 17:51:42 GMT
Data Views
Filters
Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.- Monthly Climatology calculates a monthly climatology by averaging over all years.
- anomalies calculates the difference between the (above) monthly climatology and the original data.
- Integrate along
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units