data: root mean sq anom mean $partialdiff sub time$ [ UY prec ]

root mean sq anom mean ∂_time [ UY prec ] : ∂_time Precipitacion data

prec prec prec partial_time partial_time ∂_time Precipitacion from UY: PRECM_UY_v1p1: Gridded precipitation dataset at 30 km. It corresponds to Experiment No. 3 in the documentation.

Independent Variables (Grids)

lat: grid: /lat (degree_north) ordered (29.5S) to (36S) by 0.2826087 N= 24 pts :grid

Other Info

bufferwordsize

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-999.0

missing_value

NaN

units

0.144 meter year^-2

history

root mean sq anom mean $partialdiff sub time$ [ UY prec ]

Averaged over lon[59W, 53.5W] minimum 0.0% data present
Averaged over time[Feb 1925, Nov 2009] minimum 0.0% data present

References

Muñoz, ?~A.G., González, P., Baethgen, W.,: Gridded precipitation dataset ff or Uruguay. Version 1.1

Last updated: Sun, 02 Jun 2024 17:51:42 GMT

Data Views

	lat
UY[prec precipitacion ]
root mean sq anom mean $partialdiff sub time$ [ UY prec ] [ \| lat]	M

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 lat
Differentiate along lat
Take differences along lat