data: root mean sq [ UCSB CHIRPS v2p0 daily global 0p05 prcp ]

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root mean sq [ UCSB CHIRPS v2p0 daily global 0p05 prcp ]: precipitation data

CHIRPS v2p0 daily global 0p05 prcp 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

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

mm /day

standard units*

1.15740740740741×10^-08 meter second^-1

history

root mean sq [ UCSB CHIRPS v2p0 daily global 0p05 prcp ]

created by Climate Hazards Group
Averaged over X[180W, 180] T[1200 31 Dec 1980 - 1200 1 Jan 1981, 2400 1 May 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: Tue, 01 Jul 2025 00:00:00 GMT

Data Views

	Y
root mean sq [ UCSB CHIRPS v2p0 daily global 0p05 prcp ][ 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