data: root mean sq [ IRI Forecast SST_OBS-PRECIP

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root mean sq [ IRI Forecast SST_OBS-PRECIP_GPCC History YInputData ]: YInputData data

YInputData YInputData from IRI Forecast SST_OBS-PRECIP_GPCC History: Predicand, Hindcast and Skill.

Independent Variables (Grids)

Forecast Issue Date (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 May 2026) by 1.0 N= 317 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (59.5W) to (52.5W) by 1.0 N= 8 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (29.5S) to (35.5S) by 1.0 N= 7 pts :grid

Other Info

bufferwordsize: 8
CE: null
colorscalename: precip_colors
CS: null
datatype: doublearraytype
file_missing_value: -999.0
maxncolor: 254
missing_value: NaN
pointwidth: 3.0
units: mm /month
standard units*: 0.012 meter year^-1
history: Averaged over T2[1982, 2013] L[0.0 months, 5.0 months] minimum 0.0% data present

Last updated: Mon, 31 Jul 2017 15:28:00 GMT
Expires: Sat, 05 Aug 2017 00:00:00 GMT

Data Views

	S	X	Y
doc[]
root mean sq [ IRI Forecast SST_OBS-PRECIP_GPCC History YInputData ][ X Y S \|]	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 S
Differentiate along X Y S
Take differences along X Y S