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root mean sq ∂Y [ ENACTS version0 dekadal rainfall rfe_merged_vs_meanrfe_merged ] : ∂Y Rainfall data Expressed as Percentages of the Long-Term Average data
dekadal rainfall rfe_merged_vs_meanrfe_merged partial_Y partial_Y ∂Y Rainfall data Expressed as Percentages of the Long-Term Average from ENACTS version0: version 0: CHIRPS-BLENDED and CRU.Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) ordered [ (6-15 Jan 1981) (0000 16 Jan 1981 - 1200 26 Jan 1981) (1200 26 Jan 1981 - 2400 5 Feb 1981) ... (0000 16 Mar 2024 - 1200 26 Mar 2024)] N= 1556 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- maxncolor
- 254
- units
- 0.572957795130823 radian-1 north
- history
- root mean sq $partialdiff sub Y$ [ ENACTS version0 dekadal rainfall rfe_merged_vs_meanrfe_merged ]
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Averaged over X[21.83E, 51.48E] Y[11.775S, 23.125N]
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Last updated: Fri, 19 Apr 2024 06:43:57 GMT
Expires: Thu, 11 Apr 2024 00:00:00 GMT
Data Views
Views
line plots
color bars
scatter| T | |
 root mean sq $partialdiff sub Y$ [ ENACTS version0 dekadal rainfall rfe_merged_vs_meanrfe_merged ] [ | T] | 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 T
- Differentiate along T
- Take differences along T
RMS (root mean square with mean *not* removed) over T |
RMSA (root mean square with mean removed) over T |
Maximum over T |
Minimum over T |
Detrend (best-fit-line) over T |
Note on units