served from 129.236.110.25
min mean ∂C [ OLE2 CPT ESCENARIO2 ODDS ] : ∂C ODDS data
min mean ∂C [ OLE2 CPT ESCENARIO2 ODDS ] .Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- Longitud (longitude)
- grid: /X (degree_east) ordered (117.75W) to (28.25W) by 0.5 N= 180 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (32.75N) to (62.75S) by 0.5 N= 192 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- pointwidth
- 0
- units
- percent /ids
- history
- min mean $partialdiff sub C$ [ OLE2 CPT ESCENARIO2 ODDS ]
- Averaged over C[, ] minimum 0.0% data present
min over S[0000 1 Jan 2000, 0000 1 Mar 2025]
- Averaged over C[, ] minimum 0.0% data present
Last updated: Thu, 06 Mar 2025 07:30:01 GMT
Expires: Sat, 05 Apr 2025 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts
OLE2 CPT ESCENARIO2[
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
- Differentiate along X Y
- Take differences along X Y
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |
Note on units