served from maproom.metmalawi.gov.mw
mean [ ∫dT ( UCSB CHIRPS v1p8 monthly global precipitation ) anomalies ]: CHIRPS precipitation data
CHIRPS v1p8 monthly global precipitation precipitation int_dT int_dT CHIRPS precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (0000 1 Jan 1981) to (0000 1 May 2025) by 1.0 N= 533 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (49.95N) to (49.95S) by 0.05 N= 1999 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
- mm
- standard units*
- 0.001 meter
- history
- mean [ $integral dT$ ( UCSB CHIRPS v1p8 monthly global precipitation ) anomalies ]
- Averaged over T2[16 Dec 1980 - 15 Dec 1981, 16 Dec 2023 - 15 Dec 2024] minimum 0.0% data present
Averaged over X[179.975E, 179.975E] minimum 0.0% data present
- Averaged over T2[16 Dec 1980 - 15 Dec 1981, 16 Dec 2023 - 15 Dec 2024] 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
Views
data as colors
data as contours
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 T
- Differentiate along Y T
- Take differences along Y T
RMS (root mean square with mean *not* removed) over Y T | Y T |
RMSA (root mean square with mean removed) over Y T | Y T |
Maximum over Y T | Y T |
Minimum over Y T | Y T |
Detrend (best-fit-line) over Y T | Y T |
Note on units