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root mean sq ∂Y [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation ] : ∂Y Precipitation data
root mean sq ∂Y [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation ] .Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (16 Jan 2006 - 15 Feb 2006) to (16 Nov 2100 - 15 Dec 2100) by 1.0 N= 1139 pts :grid
- longitude (longitude)
- grid: /X (degree_east) ordered (21.84E) to (51.39E) by 0.05 N= 592 pts :grid
Other Info
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- realarraytype
- file_missing_value
- 1.00000002E20
- maxncolor
- 254
- missing_value
- NaN
- units
- 57.2957795130823 kilogram meter-1 radian-1 north second-2
- history
- Averaged over Y[11.74S, 22.91N] minimum 0.0% data present
Last updated: Wed, 07 Jun 2017 11:01:55 GMT
Data Views
Views
data as colors
data as contours| T | X | |
 root mean sq $partialdiff sub Y$ [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation ] [ X | T] | 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 T
- Differentiate along X T
- Take differences along 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