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∂Y root mean sq [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation ] : ∂Y Precipitation data
∂Y root mean sq [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation ] .Independent Variables (Grids)
- longitude (longitude)
- grid: /X (degree_east) ordered (21.84E) to (51.39E) by 0.05 N= 592 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (11.715S) to (22.885N) by 0.05 N= 693 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 T[Jan 2006, Dec 2100] minimum 0.0% data present
Last updated: Wed, 07 Jun 2017 11:01:55 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| X | Y | |
 $partialdiff sub Y$ root mean sq [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation ] [ X Y |] | M | 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 X Y
- Differentiate along X Y
- Take differences along X Y
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |
Note on units