data: $partialdiff sub X$ root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMED ]

served from 129.236.110.25

∂_X root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMED ] : ∂_X Probabilidades -Temperatura Media data

∂_X root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMED ] .

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
Longitude (longitude): grid: /X (degree_east) ordered (117.5W) to (28.5W) by 0.5 N= 179 pts :grid

Other Info

CE

null

colorscalename

halfgreyscale

CS

null

datatype

realarraytype

file_missing_value

fnname

maskle

maxncolor

254

missing_value

NaN

pointwidth

units

ids /degree_east

history

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

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

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

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

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

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

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

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

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

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

$partialdiff sub X$ root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMED ]

Averaged over Y[32.75N, 62.75S] 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	X
OLE2 CPT ESCENARIO2[PROPENSIONTMED SPEARMANTMIN ABOVETMAX BELOWTMED BELOWWET ABOVETMIN ABOVE BELOWTMAX ODDSTMAX ODDS ODDSTMIN AFC AFCTMED BELOWTMIN SPEARMANTMED PROPENSION PROBABILIDADESTMED TMED PROPENSIONTMIN SPEARMANTMAX TMIN BELOW PROBABILIDADES WETDAY AFCTMIN PROPENSIONTMAX PRECIPITACION SPEARMANWET ODDSTMED PROBABILIDADESWETDAYS target_date AFCTMAX PROBABILIDADESTMIN ABOVEWET PROBABILIDADESTMAX TMAX ODDSWETDAYS AFCWET ABOVETMED PROPENSIONWETDAYS SPEARMAN ]
$partialdiff sub X$ root mean sq anom [ OLE2 CPT ESCENARIO2 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

∂X root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMED ] : ∂X Probabilidades -Temperatura Media data

Independent Variables (Grids)

Other Info

Data Views

Filters

∂_X root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMED ] : ∂_X Probabilidades -Temperatura Media data