data: mean mean $partialdiff sub lon$ $partialdiff sub lat$ $partialdiff sub time$ [ UY precipitacion ]

mean mean ∂_lon ∂_lat ∂_time [ UY precipitacion ] : ∂_lon ∂_lat ∂_time Precipitacion data

precipitacion partial_time partial_time partial_time partial_lat partial_lat partial_lon partial_lon partial_lon ∂_lon ∂_lat ∂_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 (29.78261S) to (35.71739S) by 0.2826087 N= 22 pts :grid

Other Info

bufferwordsize

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-999.0

missing_value

NaN

units

472.724114401691 meter radian^-2 north year^-2

history

mean mean $partialdiff sub lon$ $partialdiff sub lat$ $partialdiff sub time$ [ UY precipitacion ]

Averaged over time[Feb 1925, Nov 2009] minimum 0.0% data present
Averaged over lon[58.71053W, 53.78947W] 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
mean mean $partialdiff sub lon$ $partialdiff sub lat$ $partialdiff sub time$ [ UY precipitacion ] [ \| 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