served from dlibrary.snia.gub.uy
max [ L , max mean ( MGAP CPT PredErrorVars ) ]: Forecast Lead Time in Months, prediction error variance data
max [ L , max mean ( MGAP CPT PredErrorVars ) ].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
- Start time (forecast_reference_time)
- 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
- Longitude (longitude)
- grid: /X (degree_east) ordered (59.5W) to (52.5W) by 0.5 N= 15 pts :grid
Other Info
- datatype
- realarraytype
- fnname
- max
- gridid
- 183234832
- missing_value
- NaN
- pointwidth
- 3.0
- scale_max
- null
- scale_min
- null
- units
- months
- standard units*
- 0.0833333333333333 year
- history
- mean [ MGAP CPT PredErrorVars ] 4.5 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
Averaged over Y[36S, 29S] minimum 0.0% data present
max mean [ MGAP CPT PredErrorVars ]- max over L[2.5 months, 4.5 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
Views
data as colors
data as contours
line plots
color bars| L | S | X | |
 doc[] | |||
| MGAP CPT[Forecast
PredErrorVars
hindcast_date
InputObs
CFSv2_AtlPac_sst
CrossValHind
PearsonR
target_date
] | |||
| grid: /X (degree_east) ordered (59.75W) to (52.25W) by 0.5 N= 16 pts :grid | O=0.25 | ||
|---|---|---|---|
| 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 | ||
 max [ L , max mean ( MGAP CPT PredErrorVars ) ][ | L X S] | 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 L X S
- Differentiate along L X S
- Take differences along L X S
RMS (root mean square with mean *not* removed) over L X S | L X L S X S | L X S |
RMSA (root mean square with mean removed) over L X S | L X L S X S | L X S |
Maximum over L X S | L X L S X S | L X S |
Minimum over L X S | L X L S X S | L X S |
Detrend (best-fit-line) over L X S | L X L S X S | L X S |
Note on units