data: MGAP CPT hindcast

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MGAP CPT hindcast_date: hindcast time data

MGAP CPT hindcast time from SOURCES: datos de MGAP SNIA prueba.

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered (2.5 months) to (4.5 months) by 1.0 N= 3 pts :grid
Time (time): grid: /T (months since 01-Jan) ordered (Sep) to (Nov) by 1.0 N= 3 pts :grid
Training period: grid: /T2 (months since 1960-01-01) ordered (1980) to (2011) by 12.0 N= 32 pts :grid

Other Info

calendar: 360
CE: null
CS: null
datatype: realarraytype
gridid: 184899160
pointwidth: 3
units: months since 1960-01-01
standard units*: 0.0833333333333333 ( years since 1960-01-01 00:00.000000000 )

Last updated: Thu, 04 Feb 2016 15:18:08 GMT

Data Views

	L	S	T	T2	X	Y
MGAP CPT[target_date CrossValHind PearsonR PredErrorVars CFSv2_AtlPac_sst hindcast_date Forecast InputObs ]
grid: /X (degree_east) ordered (59.75W) to (52.25W) by 0.5 N= 16 pts :grid					M
grid: /Y (degree_north) ordered (29.25S) to (35.75S) by 0.5 N= 14 pts :grid						M
grid: /S (months since 1960-01-01) ordered [ (0000 1 Sep 2012) (0000 1 Oct 2012) (0000 1 Nov 2012) (0000 1 Sep 2013) (0000 1 Oct 2013) (0000 1 Nov 2013)] :grid		M
grid: /L (months) ordered (2.5 months) to (4.5 months) by 1.0 N= 3 pts :grid	M
MGAP CPT PredErrorVars[ X Y \| S L]	M	M			M	M
MGAP CPT hindcast_date[ T2 T L \|]	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 T2 T L
Differentiate along T2 T L
Take differences along T2 T L