data: $integral dL$ [ IRI Forecast_old SST_CFSV2-PRECIP

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∫dL [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History 2AFC ]: 2AFC data

2AFC 2AFC from IRI Forecast_old SST_CFSV2-PRECIP_GPCC History: Predicand, Hindcast and Skill.

Independent Variables (Grids)

L: grid: /L (months) ordered (1.0 months) to (4.0 months) by 1.0 N= 4 pts :grid
Forecast Issue Date (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2015) to (0000 1 Mar 2017) by 1.0 N= 27 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: months
standard units*: 0.0833333333333333 year

Last updated: Wed, 08 Mar 2017 14:24:39 GMT

Data Views

	L	S	X	Y
$integral dL$ [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History 2AFC ][ X Y \| S L]	M	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 L
Differentiate along X Y S L
Take differences along X Y S L