served from 129.236.110.25
min [ ALISIOS NextGen CHIRPS Seasonal OLE2 NCEP-CFSv2 Skill Pearson ]: Pearson - CCA Deterministic Hindcasts data
Pearson Pearson Pearson - CCA Deterministic Hindcasts from ALISIOS NextGen CHIRPS Seasonal OLE2 NCEP-CFSv2 Skill: Forecast Skills.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
- Longitud (longitude)
- grid: /X (degree_east) ordered (117.6837W) to (28.2837W) by 0.1 N= 895 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (32.6663N) to (49.975S) by 0.10005 N= 827 pts :grid
Other Info
- CE
- 1
- colorscalename
- correlationcolorscale
- CS
- -1
- datatype
- realarraytype
- file_missing_value
- -999
- maxncolor
- 254
- missing_value
- NaN
- scale_max
- 1.0
- scale_min
- -1.0
- history
- min over S[Jan 1960, Dec 1960]
- colorscale
Last updated: Wed, 15 Apr 2026 13:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts
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 Y L
- Differentiate along X Y L
- Take differences along X Y L
RMS (root mean square with mean *not* removed) over X Y L | X Y X L Y L | X Y L |
RMSA (root mean square with mean removed) over X Y L | X Y X L Y L | X Y L |
Maximum over X Y L | X Y X L Y L | X Y L |
Minimum over X Y L | X Y X L Y L | X Y L |
Detrend (best-fit-line) over X Y L | X Y X L Y L | X Y L |
Note on units