data: root mean sq anom $partialdiff sub T$ [ UCSB CHIRPS v1p8 monthly global precipitation ]

root mean sq anom ∂_T [ UCSB CHIRPS v1p8 monthly global precipitation ] : ∂_T CHIRPS precipitation data

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

Independent Variables (Grids)

Latitude (latitude): grid: /Y (degree_north) ordered (49.975N) to (49.975S) by 0.05 N= 2000 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: 0.144 meter year^-2
history: Averaged over X[180W, 179.95E] T[16 Jan 1981 - 15 Feb 1981, 16 Mar 2025 - 15 Apr 2025] minimum 0.0% data present

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 Jun 2025 00:00:00 GMT

Data Views

	Y
root mean sq anom $partialdiff sub T$ [ UCSB CHIRPS v1p8 monthly global precipitation ] [ Y \|]	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 Y
Differentiate along Y
Take differences along Y