served from dlibrary.snia.gub.uy
min ∂L [ MGAP CPT PredErrorVars ] : ∂L prediction error variance data
MGAP CPT PredErrorVars partial_L ∂L prediction error variance from SOURCES: datos de MGAP SNIA prueba. isIndependent Variables (Grids)
Other Info
- bufferwordsize
- 4
- CE
- null
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- pointwidth
- 3.0
- units
- 0.144 meter year-2
- history
- min $partialdiff sub L$ [ 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
min over X[59.75W, 52.25W] Y[29.25S, 35.75S] S[0000 1 Sep 2012, 0000 1 Nov 2013] L[3.0 months, 4.0 months]
- 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
Last updated: Thu, 04 Feb 2016 15:18:08 GMT
Data Views
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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units