served from 129.236.110.25
min min ∫dtime ∂lat root mean sq [ UY prec ] : ∂lat Precipitacion data
prec prec prec partial_lat int_dtime min ∂lat 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
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- units
- 0.0572957795130823 meter radian-1 north
- history
- min $integral dtime$ $partialdiff sub lat$ root mean sq [ UY prec ]
- Averaged over lon[59W, 53.5W] minimum 0.0% data present
min over lat[29.6413S, 35.8587S]
min min $integral dtime$ $partialdiff sub lat$ root mean sq [ UY prec ]- min over time[0000 1 Jan 1925, 0000 1 Jan 2010]
- Averaged over lon[59W, 53.5W] 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