data: ICPAC Projections RCA-MPI rcp26 monthly GHA rainfall precipitation climatology

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ICPAC Projections RCA-MPI rcp26 monthly GHA rainfall precipitation climatology: Precipitation data

ICPAC Projections RCA-MPI rcp26 monthly GHA rainfall precipitation climatology.

Independent Variables (Grids)

Time (time): grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid
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

CE: null
colorscalename: precip_colors
CS: null
datatype: realarraytype
file_missing_value: 1.00000002E20
maxncolor: 254
missing_value: NaN
units: kg /m /s²
standard units*: kilogram meter^-1 second^-2
history: Averaged over T2[2006, 2100] minimum 0.0% data present

Last updated: Wed, 07 Jun 2017 10:44:03 GMT

Data Views

	T	X	Y
grid: /X (degree_east) ordered (21.84E) to (51.39E) by 0.05 N= 592 pts :grid		O=-0.02499962
grid: /Y (degree_north) ordered (11.74S) to (22.91N) by 0.05 N= 694 pts :grid			M
grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid	M
ICPAC Projections RCA-MPI rcp26 monthly GHA rainfall precipitation climatology[ X Y T \|]	M	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 T
Differentiate along X Y T
Take differences along X Y T