∫dS mean ∫dL [ MGAP CPT PredErrorVars ] : prediction error variance data
MGAP CPT PredErrorVars int_dL int_dL prediction error variance from SOURCES: datos de MGAP SNIA prueba.
Independent Variables (Grids)
S (forecast_reference_time)
grid: /S (months since 1960-01-01) ordered [ (0000 16 Aug 2012) (0000 16 Sep 2012) (0000 16 Oct 2012) (0000 1 Apr 2013) (0000 16 Sep 2013) (0000 16 Oct 2013) (0000 16 Nov 2013)] :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 (29.25S) to (35.75S) by 0.5 N= 14 pts :grid
Other Info
bufferwordsize
8
CE
null
CS
null
datatype
doublearraytype
file_missing_value
-999.0
missing_value
NaN
pointwidth
3.0
units
8.33333333333333×10-05 meter year
history
$integral dS$ mean $integral dL$ [ MGAP CPT PredErrorVars ]
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 Averaged over L[2.0 months, 5.0 months] minimum 0.0% data present
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.