data: max root mean sq anom $partialdiff sub lon$ [ UY prec ]

max root mean sq anom ∂_lon [ UY prec ] : ∂_lon Precipitacion data

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

Independent Variables (Grids)

lon: grid: /lon (degree_east) ordered (58.85526W) to (53.64474W) by 0.2894737 N= 19 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 east year^-1

history

max root mean sq anom $partialdiff sub lon$ [ UY prec ]

Averaged over lat[29.5S, 36S] minimum 0.0% data present
max over time[16 Jan 1925 - 15 Feb 1925, 16 Nov 2009 - 15 Dec 2009]

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

	lon
UY[prec precipitacion ]
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: /lon (degree_east) ordered (58.85526W) to (53.64474W) by 0.2894737 N= 19 pts :grid	M
grid: /lat (degree_north) ordered (29.5S) to (36S) by 0.2826087 N= 24 pts :grid
max root mean sq anom $partialdiff sub lon$ [ UY prec ] [ lon \|]	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 lon
Differentiate along lon
Take differences along lon