data: $partialdiff sub Y$ $integral dY$ $partialdiff sub T$ [ UCSB CHIRPS v1p8 monthly global precipitation ] climatology

∂_Y ∫dY ∂_T [ UCSB CHIRPS v1p8 monthly global precipitation ] climatology: ∂_Y ∂_T CHIRPS precipitation data

CHIRPS v1p8 monthly global precipitation partial_T int_dY partial_Y ∂_Y ∂_T CHIRPS precipitation from UCSB: UC Santa Barbara.

Independent Variables (Grids)

Time (time): grid: /T (months since 01-Jan) periodic (16 Jan - 15 Feb) to (16 Dec - 15 Jan) by 1.0 N= 12 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (180W) to (179.95E) by 0.05 N= 7200 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (49.975N) to (49.975S) by 0.05 N= 2000 pts :grid

Other Info

CE: null
colorscalename: prcp_monthlyrate_max1500_smooth
CS: null
datatype: realarraytype
file_missing_value: -9999.0
maxncolor: 254
missing_value: NaN
pointwidth: 1.0
standard_name: lwe_precipitation_rate
units: 0.144 meter year^-2
history: Averaged over T2[16 Jan 1981 - 15 Jan 1982, 16 Jan 2024 - 15 Jan 2025] minimum 0.0% data present

References

Funk_etal2014

Last updated: Thu, 02 Nov 2023 07:43:25 GMT
Expires: Sun, 01 Feb 2026 00:00:00 GMT

Data Views

	T	X	Y
$partialdiff sub Y$ $integral dY$ $partialdiff sub T$ [ UCSB CHIRPS v1p8 monthly global precipitation ] climatology[ X Y T \|]	M	M	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 X Y T
Differentiate along X Y T
Take differences along X Y T