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detrended-bfl root mean sq ∫dY [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMAX ] : Probabilidades -Temperatura Máxima data
detrended-bfl root mean sq ∫dY [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMAX ] .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
- Latitude (latitude)
- grid: /Y (degree_north) ordered (33N) to (63S) by 0.5 N= 193 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- halfgreyscale
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 0
- fnname
- maskle
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- ids degree_north
- history
- [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX ) - 1. ] * 11. } , 10 , 12 ) ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 22 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Sobre la Normal ]
dominant_class over TMAX[<35, >80]
- masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Sobre la Normal ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Normal ] + masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 10 , 12 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Normal ]
dominant_class over TMAX[<35, >80]
- masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Normal ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 22 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Bajo la Normal ] + maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 0 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Bajo la Normal ]
dominant_class over TMAX[<35, >80]
- maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMAX ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]
- dominant_class [ OLE2 CPT ESCENARIO1 TMAX Bajo la Normal ]
- Averaged over S[0000 1 Jan 2000, 0000 1 Mar 2025] minimum 0.0% data present
- [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMAX ) - 1. ] * 11. } , 10 , 12 ) ]
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| L | X | Y | |
 detrended-bfl root mean sq $integral dY$ [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMAX ] 2.5 months[ X Y L |] | M | M | M |
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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