data: min $partialdiff sub time$ root mean sq $partialdiff sub time$ $integral dlon$ $partialdiff sub lon$ [ UY prec ]

min ∂_time root mean sq ∂_time ∫dlon ∂_lon [ UY prec ] : ∂_time ∂_time ∂_lon Precipitacion data

prec prec partial_lon int_dlon partial_time partial_time partial_time ∂_time ∂_time ∂_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)

time: grid: /time (months since 1960-01-01) ordered (Feb 1925) to (Nov 2009) by 1.0 N= 1018 pts :grid

Other Info

CE

null

CS

null

datatype

realarraytype

file_missing_value

-999.0

missing_value

NaN

units

1.728 meter year^-3

history

min $partialdiff sub time$ root mean sq $partialdiff sub time$ $integral dlon$ $partialdiff sub lon$ [ UY prec ]

Averaged over lon[59W, 53.5W] minimum 0.0% data present
min over lat[29.5S, 36S]

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
min $partialdiff sub time$ root mean sq $partialdiff sub time$ $integral dlon$ $partialdiff sub lon$ [ 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