data: max [ ( OLE2 CPT ESCENARIO2 SPEARMANWET ) , max ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ]

served from 129.236.110.25

max [ ( OLE2 CPT ESCENARIO2 SPEARMANWET ) , max ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ]: Spearman Días Lluviosos, Probabilidades -Temperatura Mínima data

max [ ( OLE2 CPT ESCENARIO2 SPEARMANWET ) , max ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ].

Independent Variables (Grids)

Hecho en (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 Dec 2025) by 1.0 N= 312 pts :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

CE

1.0

CS

-1.0

datatype

realarraytype

file_missing_value

-999.0

fnname

max

missing_value

NaN

pointwidth

scale_max

1.0

scale_min

-1.0

units

unitless

history

[ dominant_class ( OLE2 CPT ESCENARIO2 TMIN Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO2 TMIN ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO2 TMIN Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO2 TMIN ) - 1. ] * 11. } , 10 , 12 ) ]

dominant_class [ OLE2 CPT ESCENARIO2 TMIN Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 TMIN ] - 1. } * 11. ) , 22 ]

dominant_class [ OLE2 CPT ESCENARIO2 TMIN Sobre la Normal ]
dominant_class over TMIN[<35, >80]

masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 TMIN ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

dominant_class [ OLE2 CPT ESCENARIO2 TMIN Normal ] + masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO2 TMIN ] - 1. } * 11. ) , 10 , 12 ]

dominant_class [ OLE2 CPT ESCENARIO2 TMIN Normal ]
dominant_class over TMIN[<35, >80]

masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO2 TMIN ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

dominant_class [ OLE2 CPT ESCENARIO2 TMIN Bajo la Normal ] + maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 TMIN ] - 1. } * 11. ) , 0 ]

dominant_class [ OLE2 CPT ESCENARIO2 TMIN Bajo la Normal ]
dominant_class over TMIN[<35, >80]

maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 TMIN ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

max [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ]

max over X[117.75W, 28.25W]

Last updated: Sat, 06 Dec 2025 07:30:02 GMT
Expires: Mon, 05 Jan 2026 00:00:00 GMT

Data Views

	S	X	Y
OLE2 CPT ESCENARIO2[SPEARMANWET AFC PROPENSIONTMAX SPEARMANTMAX PROPENSIONTMIN BELOWWET ODDSTMED ABOVEWET WETDAY target_date AFCWET ABOVETMIN AFCTMED PROBABILIDADESTMAX TMAX AFCTMAX PROPENSIONWETDAYS ODDSWETDAYS ABOVETMED ODDS PROPENSIONTMED PROBABILIDADESTMIN ABOVE AFCTMIN ABOVETMAX ODDSTMIN ODDSTMAX PROBABILIDADES PROPENSION PROBABILIDADESTMED BELOWTMAX TMED BELOW SPEARMAN SPEARMANTMED BELOWTMIN TMIN PROBABILIDADESWETDAYS BELOWTMED PRECIPITACION SPEARMANTMIN ]
max [ ( OLE2 CPT ESCENARIO2 SPEARMANWET ) , max ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ][ Y \| X S]	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 Y X S
Differentiate along Y X S
Take differences along Y X S