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∫dT ∂Y [ ICPAC Projections RCA-MPI hist monthly GHA rainfall precipitation ] : ∂Y Precipitation data
∫dT ∂Y [ ICPAC Projections RCA-MPI hist monthly GHA rainfall precipitation ] .Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) ordered [ (1200 16 Dec 1950 - 1200 16 Jan 1951) (1200 16 Jan 1951 - 2400 14 Feb 1951) (0000 15 Feb 1951 - 1200 16 Mar 1951) ... (1200 16 Dec 2005 - 1200 16 Jan 2006)] N= 661 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 (11.715S) to (22.885N) by 0.05 N= 693 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
- 4950355.34993031 kilogram meter-1 radian-1 north second-1
Last updated: Thu, 17 Dec 2020 09:40:23 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $integral dT$ $partialdiff sub Y$ [ ICPAC Projections RCA-MPI hist monthly GHA rainfall precipitation ] [ 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