served from 129.236.110.25
root mean sq anom max [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMIN ] : Probabilidades -Temperatura Mínima data
root mean sq anom max [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMIN ] . isIndependent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :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
- history
- [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN ) - 1. ] * 11. } , 10 , 12 ) ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 22 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Sobre la Normal ]
dominant_class over TMIN[<35, >80]
- masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Sobre la Normal ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Normal ] + masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 10 , 12 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Normal ]
dominant_class over TMIN[<35, >80]
- masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Normal ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 22 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Bajo la Normal ] + maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 0 ]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Bajo la Normal ]
dominant_class over TMIN[<35, >80]
- maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMIN ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]
- dominant_class [ OLE2 CPT ESCENARIO1 TMIN Bajo la Normal ]
- max over X[117.75W, 28.25W] Y[32.75N, 62.75S]
root mean sq anom max [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMIN ]- Averaged over S[0000 1 Jan 2000, 0000 1 Mar 2025] minimum 0.0% data present
- [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMIN ) - 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
| L | S | X | Y | |
 OLE2 CPT ESCENARIO1[AFCTMAX
PROBABILIDADESTMIN
ABOVEWET
BELOWTMED
TMAX
PROBABILIDADESTMAX
AFCWET
ODDSWETDAYS
PROPENSIONWETDAYS
SPEARMAN
AFCTMED
PROPENSIONTMED
SPEARMANTMIN
BELOWWET
ABOVETMAX
ABOVETMIN
BELOWTMAX
ABOVE
ODDS
ODDSTMAX
ODDSTMIN
AFC
BELOWTMIN
SPEARMANTMED
PROPENSION
TMED
PROBABILIDADESTMED
PROPENSIONTMIN
SPEARMANTMAX
TMIN
BELOW
PROBABILIDADES
WETDAY
AFCTMIN
PROPENSIONTMAX
PRECIPITACION
SPEARMANWET
ODDSTMED
ABOVETMED
PROBABILIDADESWETDAYS
target_date
] | ||||
| grid: /X (degree_east) ordered (117.75W) to (28.25W) by 0.5 N= 180 pts :grid | M | |||
|---|---|---|---|---|
| grid: /Y (degree_north) ordered (32.75N) to (62.75S) by 0.5 N= 192 pts :grid | M | |||
| grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 Mar 2025) by 1.0 N= 303 pts :grid | M | |||
| OLE2 CPT ESCENARIO1 ABOVE[ X Y | S] | M | M | M | |
 root mean sq anom max [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMIN ] 2.5 months[ L |] | 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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units