data: max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO1 PROPENSIONTMED ) ]

served from 129.236.110.25

max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO1 PROPENSIONTMED ) ]: Hecho en, Propensión -Temperatura Media data

max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO1 PROPENSIONTMED ) ].

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

Other Info

calendar

360

datatype

realarraytype

fnname

max

gridid

175495832

missing_value

NaN

pointwidth

scale_max

null

scale_min

null

standard_name

forecast_reference_time

units

months since 1960-01-01

standard units*

0.0833333333333333 ( years since 1960-01-01 00:00.000000000 )

history

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

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

dominant_class [ OLE2 CPT ESCENARIO1 ODDSTMED Sobre la Normal ]
dominant_class over ODDSTMED[0, >9.0]

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

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

dominant_class [ OLE2 CPT ESCENARIO1 ODDSTMED Normal ]
dominant_class over ODDSTMED[0, >9.0]

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

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

dominant_class [ OLE2 CPT ESCENARIO1 ODDSTMED Bajo la Normal ]
dominant_class over ODDSTMED[0, >9.0]

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

root mean sq anom [ OLE2 CPT ESCENARIO1 PROPENSIONTMED ] 0000 1 Dec 2025

Averaged over X[117.75W, 28.25W] minimum 0.0% data present

max root mean sq anom [ OLE2 CPT ESCENARIO1 PROPENSIONTMED ]

max over Y[32.75N, 62.75S] S[0000 1 Jan 2000, 0000 1 Dec 2025]

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

Data Views

	S
OLE2 CPT ESCENARIO1[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 ]
grid: /X (degree_east) ordered (117.75W) to (28.25W) by 0.5 N= 180 pts :grid
grid: /Y (degree_north) ordered (32.75N) to (62.75S) by 0.5 N= 192 pts :grid
max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO1 PROPENSIONTMED ) ][ \| S]	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 S
Differentiate along S
Take differences along S