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∫dY [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation anomalies ]: Precipitation data
∫dY [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation anomalies ].Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Jan 2006) to (Dec 2100) by 1.0 N= 1140 pts :grid
- 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 (11.74S) 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
- 0.0174532925199433 kilogram meter-1 radian north second-2
- history
- Averaged over T2[2006, 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| T | X | Y | |
 $integral dY$ [ ICPAC Projections RCA-MPI rcp85 monthly GHA rainfall precipitation anomalies ][ X Y | T] | M | 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 Y T
- Differentiate along X Y T
- Take differences along X Y T
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units