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min ∫dT [ ICPAC Projections RCA-MPI rcp45 monthly GHA rainfall precipitation ] : Precipitation data
min ∫dT [ ICPAC Projections RCA-MPI rcp45 monthly GHA rainfall precipitation ] .Independent Variables (Grids)
- Longitude (longitude)
- grid: /X (degree_east) ordered (21.865E) to (51.365E) by 0.05 N= 591 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (11.74S) to (22.91N) by 0.05 N= 694 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 1.00000002E20
- maxncolor
- 254
- missing_value
- NaN
- units
- 0.0833333333333333 kilogram meter-1 second-2 year
- history
- min over T[0000 1 Jan 2006, 0000 1 Jan 2101]
Last updated: Wed, 07 Jun 2017 10:46:37 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| X | Y | |
 min $integral dT$ [ ICPAC Projections RCA-MPI rcp45 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