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

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

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

lon: grid: /lon (degree_east) ordered (59W) to (53.5W) by 0.2894737 N= 20 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 $partialdiff sub time$ mean $integral dlon$ $partialdiff sub lon$ $partialdiff sub time$ [ UY prec ]

Averaged over lat[36.1413S, 29.3587S] minimum 0.0% data present
min over time[16 Feb 1925 - 15 Mar 1925, 16 Oct 2009 - 15 Nov 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
min $partialdiff sub time$ mean $integral dlon$ $partialdiff sub lon$ $partialdiff sub time$ [ 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