data: root mean sq anom $integral dtime$ $integral dlat$ root mean sq [ UY prec ]

root mean sq anom ∫dtime ∫dlat root mean sq [ UY prec ] : Precipitacion data

prec prec prec prec int_dlat int_dtime 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 (days since 1960-01-01) ordered [ (1200 16 Dec 1924 - 1200 16 Jan 1925) (1200 16 Jan 1925 - 2400 14 Feb 1925) (0000 15 Feb 1925 - 1200 16 Mar 1925) ... (1200 16 Dec 2009 - 1200 16 Jan 2010)] N= 1021 pts :grid

Other Info

bufferwordsize

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-999.0

missing_value

NaN

units

18.0955736846772 meter radian north second year^-1

history

root mean sq anom $integral dtime$ $integral dlat$ root mean sq [ UY prec ]

Averaged over lon[59.14474W, 53.35526W] minimum 0.0% data present
Averaged over lat[29.5S, 36S] 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

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root mean sq anom $integral dtime$ $integral dlat$ root mean sq [ 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