served from maproom.metmalawi.gov.mw
∂T ∂X ∂Y [ UCSB CHIRPS v1p8 monthly global precipitation ] : ∂T ∂X ∂Y CHIRPS precipitation data
CHIRPS v1p8 monthly global precipitation precipitation partial_Y partial_X partial_X ∂T ∂X ∂Y CHIRPS precipitation from UCSB: UC Santa Barbara.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (16 Jan 1981 - 15 Feb 1981) to (16 Mar 2025 - 15 Apr 2025) by 1.0 N= 531 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic [ (179.975W) (179.925W) (179.875W) ... (179.925E)] N= 7200 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (49.89999N) to (49.89999S) by 0.04999999 N= 1997 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 1500.0
- colorscalename
- prcp_monthlyrate_max1500_smooth
- CS
- 0.0
- datatype
- realarraytype
- file_missing_value
- -9999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 1.0
- standard_name
- lwe_precipitation_rate
- units
- 472.724114401691 meter radian-2 north year-2
- 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: 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| T | X | Y | |
 $partialdiff sub T$ $partialdiff sub X$ $partialdiff sub Y$ [ UCSB CHIRPS v1p8 monthly global precipitation ] [ X Y | T] | M | 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 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