data: mean $integral dlat$ $integral dlon$ $partialdiff sub time$ [ UY prec ]

mean ∫dlat ∫dlon ∂_time [ UY prec ] : ∂_time Precipitacion data

prec prec partial_time int_dlon int_dlat ∂_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 Jan 1925 - 15 Feb 1925) to (16 Nov 2009 - 15 Dec 2009) by 1.0 N= 1019 pts :grid

Other Info

bufferwordsize: 8
CE: null
CS: null
datatype: doublearraytype
file_missing_value: -999.0
missing_value: NaN
units: 4.3864908449286×10^-05 meter radian² north year^-2
history: Averaged over lon[59.14474W, 53.35526W] lat[36.1413S, 29.3587S] 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[precipitacion prec ]
mean $integral dlat$ $integral dlon$ $partialdiff sub time$ [ 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