mean ∫dX [ MGAP CPT CFSv2_AtlPac_sst PredErrorVars ] : prediction error variance data
MGAP CPT CFSv2_AtlPac_sst PredErrorVars int_dX prediction error variance 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
Forecast Issue Date (forecast_reference_time)
grid: /S (months since 1960-01-01) ordered (0000 1 Sep 2014) to (0000 1 Oct 2014) N= 2 pts :grid
Longitude (longitude)
grid: /X (degree_east) ordered (60W) to (52W) by 1.0 N= 9 pts :grid
Other Info
bufferwordsize
8
CE
null
CS
null
datatype
doublearraytype
file_missing_value
-999.0
missing_value
NaN
pointwidth
0
units
2.02005700462307×10-10 meter radian east second-1
history
mean $integral dX$ [ MGAP CPT CFSv2_AtlPac_sst 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 Y[36S, 29S] 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.