data: detrended-bfl max [ T , max ( MGAP CPT PearsonR ) ]

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detrended-bfl max [ T , max ( MGAP CPT PearsonR ) ] : Time, Pearson correlation skill values data

detrended-bfl max [ T , max ( MGAP CPT PearsonR ) ] .

Independent Variables (Grids)

Time (time): grid: /T (months since 01-Jan) ordered (Sep) to (Nov) by 1.0 N= 3 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (59.75W) to (52.25W) by 0.5 N= 16 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (29.5S) to (35.5S) by 0.5 N= 13 pts :grid

Other Info

bufferwordsize

calendar

360

CE

null

CS

null

datatype

doublearraytype

fnname

max

gridid

183232736

missing_value

NaN

pointwidth

1.0

scale_max

null

scale_min

null

standard_name

time

units

months

standard units*

0.0833333333333333 year

history

max [ MGAP CPT PearsonR ]

Output from CPT for 12 3-month running seasons for 1960-2009 between ECHAM4p5 GCM and CRU dataset, CPT recompiled on Mac 9.04 version
max over L[2.5 months, 4.5 months]

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

Data Views

	T	X	Y
doc[]
MGAP CPT[hindcast_date InputObs target_date CrossValHind PearsonR PredErrorVars CFSv2_AtlPac_sst Forecast ]
grid: /X (degree_east) ordered (59.75W) to (52.25W) by 0.5 N= 16 pts :grid		M
grid: /Y (degree_north) ordered (29.5S) to (35.5S) by 0.5 N= 13 pts :grid			M
detrended-bfl max [ T , max ( MGAP CPT PearsonR ) ] [ \| Y T X]	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 Y T X
Differentiate along Y T X
Take differences along Y T X