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UCSB CHIRPS v1p8 daily africa 0p25 precipitation: precipitation data
CHIRPS v1p8 daily africa 0p25 precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Time (time)
- grid: /T (days since 1960-01-01 12:00:00) ordered (1 Jan 1981) to (14 Oct 2024) by 1.0 N= 15993 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (19.875W) to (54.875E) by 0.25 N= 300 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (39.875N) to (39.875S) by 0.25 N= 320 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 100.0
- colorscalename
- prcp_dailyrate_max100_smooth
- CS
- 0.0
- datatype
- realarraytype
- maxncolor
- 254
- missing_value
- -9999.0
- pointwidth
- 1
- scale_max
- 100.0
- scale_min
- 0.0
- standard_name
- lwe_precipitation_rate
- units
- mm /day
- standard units*
- 1.15740740740741×10-08 meter second-1
- colorscale
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: Wed, 29 May 2024 07:29:02 GMT
Expires: Thu, 19 Dec 2024 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 UCSB CHIRPS v1p8 daily africa 0p25[precipitation
] | |||
| UCSB CHIRPS v1p8 daily africa 0p25 precipitation[ X Y | T] | M | M | M |
|---|---|---|---|
| UCSB CHIRPS v1p8 daily africa 0p25 precipitation[ X Y | T] | M | M | M |
 UCSB CHIRPS v1p8 daily africa 0p25 precipitation[ 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
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units