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∂Y ∫dY mean [ ENACTS version0 dekadal rainfall rfe_mergeddiff ] : ∂Y Rainfall Anomaly data
dekadal rainfall rfe_mergeddiff rfe_mergeddiff rfe_mergeddiff int_dY ∂Y Rainfall Anomaly from ENACTS version0: version 0: CHIRPS-BLENDED and CRU.Independent Variables (Grids)
- Longitude (longitude)
- grid: /X (degree_east) ordered (21.855E) to (51.455E) by 0.05 N= 593 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (11.775S) to (23.125N) by 0.05 N= 699 pts :grid
Other Info
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- realarraytype
- maxncolor
- 254
- missing_value
- NaN
- units
- mm
- standard units*
- 0.001 meter
- history
- $partialdiff sub Y$ $integral dY$ mean [ ENACTS version0 dekadal rainfall rfe_mergeddiff ]
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Averaged over T[6-15 Jan 1981, 2400 25 Sep 2024] minimum 0.0% data present
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Last updated: Mon, 28 Oct 2024 09:31:03 GMT
Expires: Fri, 11 Oct 2024 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| X | Y | |
 $partialdiff sub Y$ $integral dY$ mean [ ENACTS version0 dekadal rainfall rfe_mergeddiff ] [ 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