served from kmddl.meteo.go.ke
UCSB CHIRPS v2p0 daily global 0p25 prcp: precipitation data
CHIRPS v2p0 daily global 0p25 prcp precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Time (time)
- grid: /T (days since 1960-01-01) ordered (1 Jan 1981) to (1 Nov 2024) by 1.0 N= 16011 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic (179.875W) to (179.875E) by 0.25 N= 1440 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (49.875N) to (49.875S) by 0.25 N= 400 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
- 1.0
- 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
- history
- created by Climate Hazards Group
- 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: Wed, 01 Jan 2025 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 v2p0 daily global 0p25[prcp
] | |||
| grid: /X (degree_east) periodic (179.875W) to (179.875E) by 0.25 N= 1440 pts :grid | M | ||
|---|---|---|---|
| grid: /Y (degree_north) ordered (49.875N) to (49.875S) by 0.25 N= 400 pts :grid | M | ||
| grid: /T (days since 1960-01-01) ordered (1 Jan 1981) to (1 Nov 2024) by 1.0 N= 16011 pts :grid | M | ||
 UCSB CHIRPS v2p0 daily global 0p25 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
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