served from maproom.metmalawi.gov.mw
root mean sq [ ∂T ( UCSB CHIRPS v1p8 monthly global precipitation ) anomalies ]: ∂T CHIRPS precipitation data
CHIRPS v1p8 monthly global precipitation partial_T partial_T partial_T ∂T CHIRPS precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) (360) ordered [ (1200 21 Jun 1981 - 1200 22 Jun 1981) (1200 21 Aug 1981 - 1200 22 Aug 1981) (1200 22 Oct 1981 - 1200 23 Oct 1981) ... (1202 16 Nov 2026 - 1202 17 Nov 2026)] N= 214 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (49.975N) to (49.975S) by 0.05 N= 2000 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
- 0.144 meter year-2
- history
- root mean sq [ $partialdiff sub T$ ( UCSB CHIRPS v1p8 monthly global precipitation ) anomalies ]
- Averaged over T2[16 Jan 1981 - 15 Jan 1982, 16 Jan 2024 - 15 Jan 2025] minimum 0.0% data present
Averaged over X[179.975E, 179.975E] minimum 0.0% data present
- Averaged over T2[16 Jan 1981 - 15 Jan 1982, 16 Jan 2024 - 15 Jan 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: Sun, 01 Feb 2026 00:00:00 GMT
Data Views
Views
data as colors
data as contours| T | Y | |
 root mean sq [ $partialdiff sub T$ ( UCSB CHIRPS v1p8 monthly global precipitation ) anomalies ][ Y | T] | M | M |
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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