served from maproom.metmalawi.gov.mw
root mean sq ∫dX [ ∂T ( UCSB CHIRPS v1p8 monthly global precipitation ) climatology ] : ∂T CHIRPS precipitation data
CHIRPS v1p8 monthly global precipitation partial_T partial_T int_dX ∂T CHIRPS precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Longitude (longitude)
- grid: /X (degree_east) ordered (179.975E) to (179.975E) by 0.05 N= 7201 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
- 0.00251327412287183 meter radian east year-2
- history
- root mean sq $integral dX$ [ $partialdiff sub T$ ( UCSB CHIRPS v1p8 monthly global precipitation ) climatology ]
- Averaged over T2[16 Jan 1981 - 15 Jan 1982, 16 Jan 2024 - 15 Jan 2025] minimum 0.0% data present
Averaged over T[16 Jan - 15 Feb, 16 Dec - 15 Jan] 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 Jun 2025 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| X | Y | |
 root mean sq $integral dX$ [ $partialdiff sub T$ ( UCSB CHIRPS v1p8 monthly global precipitation ) climatology ] [ X Y |] | 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 X Y
- Differentiate along X Y
- Take differences along X Y
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |
Note on units