root mean sq [ ENACTS version0 dekadal climatologies rfe ]: Dekadal rainfall climatology 1981-2010 average data
dekadal climatologies rfe Dekadal rainfall climatology 1981-2010 average from ENACTS version0: version 0: CHIRPS-BLENDED and CRU.
Independent Variables (Grids)
- Time
- grid: /T (days since 1981-01-01) (365) periodic [ (1-10 Jan) (11-20 Jan) (21-31 Jan) (1-10 Feb) (11-20 Feb) (21-28 Feb) (1-10 Mar) (11-20 Mar) (21-31 Mar) (1-10 Apr) (11-20 Apr) (21-30 Apr) (1-10 May) (11-20 May) (21-31 May) (1-10 Jun) (11-20 Jun) (21-30 Jun) (1-10 Jul) (11-20 Jul) (21-31 Jul) (1-10 Aug) (11-20 Aug) (21-31 Aug) (1-10 Sep) (11-20 Sep) (21-30 Sep) (1-10 Oct) (11-20 Oct) (21-31 Oct) (1-10 Nov) (11-20 Nov) (21-30 Nov) (1-10 Dec) (11-20 Dec) (21-31 Dec)] :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (21.855E) to (51.455E) by 0.05 N= 593 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- maxncolor
- 254
- missing_value
- NaN
- units
- mm
- standard units*
- 0.001 meter
- history
- root mean sq [ ENACTS version0 dekadal climatologies rfe ]
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
Averaged over Y[11.8S, 23.15N] minimum 0.0% data present
Last updated: Mon, 28 Oct 2024 09:31:03 GMT
Expires: Fri, 11 Oct 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 X
T
- Differentiate along X
T
- Take differences along X
T
Average over
X
T
|
X T
|
RMS (root mean square with mean *not* removed) over
X
T
|
X T
|
RMSA (root mean square with mean removed) over
X
T
|
X T
|
Maximum over
X
T
|
X T
|
Minimum over
X
T
|
X T
|
Detrend (best-fit-line) over
X
T
|
X T
|
Note on units