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root mean sq ∂T ∫dY [ ENACTS version0 dekadal rainfall rfe_mergeddiff ] : ∂T Rainfall Anomaly data
dekadal rainfall rfe_mergeddiff rfe_mergeddiff int_dY partial_T ∂T Rainfall Anomaly from ENACTS version0: version 0: CHIRPS-BLENDED and CRU.Independent Variables (Grids)
- Latitude (latitude)
- grid: /Y (degree_north) ordered (11.8S) to (23.15N) by 0.05 N= 700 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- maxncolor
- 254
- missing_value
- NaN
- units
- 2.02005700462307×10-10 meter radian north second-1
- history
- root mean sq $partialdiff sub T$ $integral dY$ [ ENACTS version0 dekadal rainfall rfe_mergeddiff ]
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Averaged over X[21.83E, 51.48E] T[0000 11 Jan 1981 - 0600 21 Jan 1981, 2400 20 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
line plots
color bars
scatter| Y | |
 root mean sq $partialdiff sub T$ $integral dY$ [ ENACTS version0 dekadal rainfall rfe_mergeddiff ] [ Y |] | M |
|---|
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
- Differentiate along Y
- Take differences along Y
RMS (root mean square with mean *not* removed) over Y |
RMSA (root mean square with mean removed) over Y |
Maximum over Y |
Minimum over Y |
Detrend (best-fit-line) over Y |
Note on units