data: $integral dT$ $integral dT$ $partialdiff sub Y$ [ UCSB CHIRPS v2p0 daily global 0p05 prcp ]

∫dT ∫dT ∂_Y [ UCSB CHIRPS v2p0 daily global 0p05 prcp ] : ∂_Y precipitation data

CHIRPS v2p0 daily global 0p05 prcp partial_Y int_dT ∂_Y precipitation from UCSB: UC Santa Barbara.

Independent Variables (Grids)

Time (time): grid: /T (julian_day) ordered (1200 31 Dec 1980) to (1200 2 Dec 2025) by 1.0 N= 16408 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (179.975W) to (179.975E) by 0.05 N= 7200 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (49.95N) to (49.95S) by 0.05 N= 1999 pts :grid

Other Info

bufferwordsize: 8
CE: null
colorscalename: prcp_dailyrate_max100_smooth
CS: null
datatype: doublearraytype
file_missing_value: -9999.0
maxncolor: 254
missing_value: NaN
pointwidth: 1.0
standard_name: lwe_precipitation_rate
units: 4950.35534993032 meter radian^-1 north second
history: created by Climate Hazards Group

References

Funk, C. C, Peterson, P. J., Landsfeld, M. F., Pedreros, D. H., Verdin, J. P., Rowland, J. D., Romero, B. E., Husak, G. J. Michaelsen, J. C., and Verdin, A. P., 2014, A quasi-global precipitation time series for drought monitoring: U. S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832.

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

Data Views

	T	X	Y
$integral dT$ $integral dT$ $partialdiff sub Y$ [ UCSB CHIRPS v2p0 daily global 0p05 prcp ] [ 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