data: mean [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMED ]

served from 129.236.110.25

mean [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMED ]: Probabilidades -Temperatura Media data

mean [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMED ].

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

Other Info

bufferwordsize

CE

null

colorscalename

halfgreyscale

CS

null

datatype

doublearraytype

file_missing_value

fnname

maskle

maxncolor

254

missing_value

NaN

pointwidth

units

ids

history

[ dominant_class ( OLE2 CPT ESCENARIO1 TMED Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMED ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO1 TMED Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO1 TMED ) - 1. ] * 11. } , 10 , 12 ) ]

dominant_class [ OLE2 CPT ESCENARIO1 TMED Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMED ] - 1. } * 11. ) , 22 ]

dominant_class [ OLE2 CPT ESCENARIO1 TMED Sobre la Normal ]
dominant_class over TMED[<35, >80]

masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMED ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

dominant_class [ OLE2 CPT ESCENARIO1 TMED Normal ] + masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMED ] - 1. } * 11. ) , 10 , 12 ]

dominant_class [ OLE2 CPT ESCENARIO1 TMED Normal ]
dominant_class over TMED[<35, >80]

masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMED ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

dominant_class [ OLE2 CPT ESCENARIO1 TMED Bajo la Normal ] + maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMED ] - 1. } * 11. ) , 0 ]

dominant_class [ OLE2 CPT ESCENARIO1 TMED Bajo la Normal ]
dominant_class over TMED[<35, >80]

maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO1 TMED ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

mean [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMED ]

Averaged over Y[63S, 33N] S[0000 1 Jan 2000, 0000 1 Mar 2025] 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

	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 ]
OLE2 CPT ESCENARIO1 BELOW[ X Y \| S]		M	M	M
OLE2 CPT ESCENARIO1 ABOVE[ X Y \| S]		M	M	M
mean [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMED ] 2.5 months[ X L \|]	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
Differentiate along X
Take differences along X

	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 ]
OLE2 CPT ESCENARIO1 BELOW[ X Y \| S]		M	M	M
OLE2 CPT ESCENARIO1 ABOVE[ X Y \| S]		M	M	M
mean [ OLE2 CPT ESCENARIO1 PROBABILIDADESTMED ] 2.5 months[ X L \|]	M		M