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∂Y root mean sq ∫dX max [ OLE2 CPT ESCENARIO2 PRECIPITACION ] : ∂Y Probabilidades - Precipitación - Categorías data
∂Y root mean sq ∫dX max [ OLE2 CPT ESCENARIO2 PRECIPITACION ] .Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (118W) to (28W) by 0.5 N= 181 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (32.5N) to (62.5S) by 0.5 N= 191 pts :grid
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -1.0
- missing_value
- NaN
- pointwidth
- 0
- units
- percent
- standard units*
- 0.01
- history
- $partialdiff sub Y$ root mean sq $integral dX$ max [ OLE2 CPT ESCENARIO2 PRECIPITACION ]
- max over S[0000 1 Jan 2000, 0000 1 May 2025]
Averaged over C[Bajo la Normal, Sobre la Normal] minimum 0.0% data present
- max over S[0000 1 Jan 2000, 0000 1 May 2025]
Last updated: Tue, 06 May 2025 06:30:01 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | X | Y | |
 $partialdiff sub Y$ root mean sq $integral dX$ max [ OLE2 CPT ESCENARIO2 PRECIPITACION ] 2.5 months[ X Y | L] | 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 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