served from dlibrary.snia.gub.uy
mean ∫dT ∂Y [ MGAP CPT CFSv2_AtlPac_sst InputObs ] : ∂Y input observations data
MGAP CPT CFSv2_AtlPac_sst InputObs partial_Y int_dT ∂Y input observations 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
- Time (time)
- grid: /T (months since 1960-01-01) ordered (0000 1 Jan 1960) to (0000 1 Jan 1961) by 1.0 N= 13 pts :grid
- Training period
- grid: /T2 (months since 1960-01-01) ordered (1980) to (2014) by 12.0 N= 35 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (35S) to (30S) by 1.0 N= 6 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 1.0
- units
- 5.52621330180192×10-08 meter radian-1 north second-1 year
- history
- mean $integral dT$ $partialdiff sub Y$ [ MGAP CPT CFSv2_AtlPac_sst InputObs ]
- 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 X[60W, 52W] minimum 0.0% data present
- 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 | T | T2 | Y | |
 MGAP CPT[PredErrorVars
hindcast_date
CFSv2_AtlPac_sst
Forecast
InputObs
target_date
CrossValHind
PearsonR
] | ||||
| grid: /X (degree_east) ordered (59.5W) to (52.5W) by 1.0 N= 8 pts :grid | ||||
| grid: /Y (degree_north) ordered (35.5S) to (29.5S) by 1.0 N= 7 pts :grid | O=0.5 | |||
| grid: /T2 (months since 1960-01-01) ordered (1980) to (2014) by 12.0 N= 35 pts :grid | M | |||
| grid: /T (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid | O=-0.5 | |||
| grid: /L (months) ordered (2.5 months) to (4.5 months) by 1.0 N= 3 pts :grid | M | |||
 mean $integral dT$ $partialdiff sub Y$ [ MGAP CPT CFSv2_AtlPac_sst InputObs ] [ Y T2 | T L] | M | 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 T2 T L
- Differentiate along Y T2 T L
- Take differences along Y T2 T L
RMS (root mean square with mean *not* removed) over Y T2 T L | Y T2 Y T Y L T2 T T2 L T L | Y T2 T Y T2 L Y T L T2 T L | Y T2 T L |
RMSA (root mean square with mean removed) over Y T2 T L | Y T2 Y T Y L T2 T T2 L T L | Y T2 T Y T2 L Y T L T2 T L | Y T2 T L |
Maximum over Y T2 T L | Y T2 Y T Y L T2 T T2 L T L | Y T2 T Y T2 L Y T L T2 T L | Y T2 T L |
Minimum over Y T2 T L | Y T2 Y T Y L T2 T T2 L T L | Y T2 T Y T2 L Y T L T2 T L | Y T2 T L |
Detrend (best-fit-line) over Y T2 T L | Y T2 Y T Y L T2 T T2 L T L | Y T2 T Y T2 L Y T L T2 T L | Y T2 T L |
Note on units