data: mean mean $partialdiff sub lat$ [ UY prec ]

mean mean ∂_lat [ UY prec ] : ∂_lat Precipitacion data

prec prec partial_lat partial_lat ∂_lat 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 (Jan 1925) to (Dec 2009) by 1.0 N= 1020 pts :grid

Other Info

bufferwordsize

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-999.0

missing_value

NaN

units

0.687549354156988 meter radian^-1 north year^-1

history

mean mean $partialdiff sub lat$ [ UY prec ]

Averaged over lat[36S, 29.5S] minimum 0.0% data present
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 1.1

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

Data Views

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