served from dlibrary.snia.gub.uy
mean [ IRI Forecast SST_OBS-PRECIP_GPCC History 2AFC ]: 2AFC data
2AFC 2AFC from IRI Forecast SST_OBS-PRECIP_GPCC History: Predicand, Hindcast and Skill.Independent Variables (Grids)
- Forecast Issue Date (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 May 2026) by 1.0 N= 317 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (59.5W) to (52.5W) by 1.0 N= 8 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
- 3.0
- units
- unitless
- standard units*
- unitless
- history
- Averaged over Y[36S, 29S] L[0.0 months, 5.0 months] minimum 0.0% data present
Last updated: Mon, 31 Jul 2017 15:28:00 GMT
Expires: Sat, 05 Aug 2017 00:00:00 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| S | X | |
 doc[] | ||
| IRI Forecast SST_OBS-PRECIP_GPCC History[target_date
InputObs
hindcast_date
PearsonR
CrossValPred
2AFC
SpearmanR
YInputData
] | ||
 mean [ IRI Forecast SST_OBS-PRECIP_GPCC History 2AFC ][ X S |] | 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 X S
- Differentiate along X S
- Take differences along X S
RMS (root mean square with mean *not* removed) over X S | X S |
RMSA (root mean square with mean removed) over X S | X S |
Maximum over X S | X S |
Minimum over X S | X S |
Detrend (best-fit-line) over X S | X S |
Note on units