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

max 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)

time: grid: /time (months since 1960-01-01) ordered (16 Feb 1925 - 15 Mar 1925) to (16 Oct 2009 - 15 Nov 2009) by 1.0 N= 1017 pts :grid

Other Info

CE

null

CS

null

datatype

realarraytype

file_missing_value

-999.0

missing_value

NaN

units

472.724114401691 meter radian^-2 north year^-2

history

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

Averaged over lon[58.85526W, 53.64474W] minimum 0.0% data present
max over lat[29.78261S, 35.71739S]

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

	time
max mean $partialdiff sub lon$ $partialdiff sub lat$ $partialdiff sub time$ [ UY precipitacion ] [ time \|]	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 time
Differentiate along time
Take differences along time