data: root mean sq $integral dY$ [ UCSB CHIRPS v1p8 dekad prcp climatology ]

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root mean sq ∫dY [ UCSB CHIRPS v1p8 dekad prcp climatology ] : precipitation data

CHIRPS v1p8 dekad prcp prcp int_dY precipitation from UCSB: UC Santa Barbara.

Independent Variables (Grids)

Time: grid: /T (months since 1960-01-01) periodic (0000 1 Jan - 0000 11 Jan) to (0000 21 Dec - 0000 1 Jan) by 0.3333335 N= 36 pts :grid

Other Info

bufferwordsize

CE

null

colorscalename

prcp_dekadrate_max600_smooth

CS

null

datatype

doublearraytype

file_missing_value

-9999.0

maxncolor

254

missing_value

NaN

standard_name

lwe_precipitation_rate

units

1.74532925199433×10^-05 meter radian north

history

root mean sq $integral dY$ [ UCSB CHIRPS v1p8 dekad prcp climatology ]

Averaged over T2[1981, 2357 30 Dec 2023 - 2357 30 Dec 2024] minimum 0.0% data present
Averaged over X[180W, 180] Y[50.025S, 50.025N] 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

	T
root mean sq $integral dY$ [ UCSB CHIRPS v1p8 dekad prcp climatology ] [ T \|]	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 T
Differentiate along T
Take differences along T