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

served from maproom.metmalawi.gov.mw

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

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

Independent Variables (Grids)

Time (time): grid: /T (months since 1960-01-01) ordered (16 Jan 1981 - 15 Feb 1981) to (16 Nov 2025 - 15 Dec 2025) by 1.0 N= 539 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 (50N) to (50S) by 0.05 N= 2001 pts :grid

Other Info

bufferwordsize: 8
CE: null
colorscalename: prcp_monthlyrate_max1500_smooth
CS: null
datatype: doublearraytype
file_missing_value: -9999.0
maxncolor: 254
missing_value: NaN
pointwidth: 1.0
standard_name: lwe_precipitation_rate
units: 0.00251327412287183 meter radian north 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
$integral dY$ $partialdiff sub T$ [ UCSB CHIRPS v1p8 monthly global precipitation ] anomalies[ 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