data: max $partialdiff sub lat$ mean $partialdiff sub lon$ $integral dlon$ [ UY prec ]

max ∂_lat mean ∂_lon ∫dlon [ UY prec ] : ∂_lat ∂_lon Precipitacion data

prec prec prec int_dlon partial_lon partial_lon partial_lat ∂_lat ∂_lon Precipitacion from UY: PRECM_UY_v1p1: Gridded precipitation dataset at 30 km. It corresponds to Experiment No. 3 in the documentation. is

Independent Variables (Grids)

Other Info

CE

null

CS

null

datatype

realarraytype

file_missing_value

-999.0

missing_value

NaN

units

0.687549354156988 meter radian^-1 north year^-1

history

max $partialdiff sub lat$ mean $partialdiff sub lon$ $integral dlon$ [ UY prec ]

Averaged over lon[59W, 53.5W] minimum 0.0% data present
max over time[16 Jan 1925 - 15 Feb 1925, 16 Nov 2009 - 15 Dec 2009] lat[29.6413S, 35.8587S]

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

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

grid: /lat (degree_north) ordered (29.6413S) to (35.8587S) by 0.2826087 N= 23 pts :grid

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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
Differentiate along
Take differences along

Average over
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over

Note on units