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

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

prec prec partial_time int_dlon int_dlon int_dlat ∂_time 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

bufferwordsize

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-999.0

missing_value

NaN

units

4.3864908449286×10^-05 meter radian² north year^-2

history

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

Averaged over lon[59.14474W, 53.35526W] minimum 0.0% data present
min over time[16 Jan 1925 - 15 Feb 1925, 16 Nov 2009 - 15 Dec 2009] lat[29.3587S, 36.1413S]

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

[ |]

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