root mean sq anom ∫dY ∂T ∂T [ ENACTS version0 dekadal rainfall rfe_merged_vs_meanrfe_merged ] : ∂T ∂T Rainfall data Expressed as Percentages of the Long-Term Average data
dekadal rainfall rfe_merged_vs_meanrfe_merged partial_T partial_T partial_T int_dY
∂T ∂T 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 [ (0300 16 Jan 1981 - 1200 26 Jan 1981) (1200 26 Jan 1981 - 2100 5 Feb 1981) (2100 5 Feb 1981 - 1800 15 Feb 1981) ... (2100 5 Apr 2024 - 2400 15 Apr 2024)] N= 1557 pts :grid
- 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
- units
- 2.33802894053596×10-14 radian north second-2
- history
- root mean sq anom $integral dY$ $partialdiff sub T$ $partialdiff sub T$ [ ENACTS version0 dekadal rainfall rfe_merged_vs_meanrfe_merged ]
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Averaged over X[21.855E, 51.455E]
Last updated: Thu, 16 May 2024 08:15:58 GMT
Expires: Sat, 11 May 2024 00:00:00 GMT
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
T
- Differentiate along Y
T
- Take differences along Y
T
Average over
Y
T
|
Y T
|
RMS (root mean square with mean *not* removed) over
Y
T
|
Y T
|
RMSA (root mean square with mean removed) over
Y
T
|
Y T
|
Maximum over
Y
T
|
Y T
|
Minimum over
Y
T
|
Y T
|
Detrend (best-fit-line) over
Y
T
|
Y T
|
Note on units