data: max $partialdiff sub Y$ min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ]

served from 129.236.110.25

max ∂_Y min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ] : ∂_Y Hecho en, Propensión - Precipitación data

max ∂_Y min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ] .

Independent Variables (Grids)

Latitude (latitude): grid: /Y (degree_north) ordered (32.5N) to (62.5S) by 0.5 N= 191 pts :grid

Other Info

calendar

360

datatype

realarraytype

fnname

min

gridid

175490048

missing_value

NaN

pointwidth

scale_max

null

scale_min

null

standard_name

forecast_reference_time

units

4.77464829275686 radian^-1 north year

history

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

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

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

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

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

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

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

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

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

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

min [ OLE2 CPT ESCENARIO1 PROPENSION ]

min over X[117.75W, 28.25W]

max $partialdiff sub Y$ min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ]

max over 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

	Y
OLE2 CPT ESCENARIO1[PROPENSIONTMIN PROBABILIDADES BELOWTMED TMED PROBABILIDADESTMED ABOVETMAX PROPENSION BELOW PROBABILIDADESWETDAYS AFCTMIN SPEARMAN TMIN AFCTMED BELOWTMAX SPEARMANTMAX PRECIPITACION PROPENSIONTMAX SPEARMANWET AFC ODDSTMED WETDAY PROBABILIDADESTMIN ABOVEWET AFCTMAX PROPENSIONWETDAYS target_date AFCWET TMAX PROBABILIDADESTMAX SPEARMANTMIN ODDSWETDAYS ODDS PROPENSIONTMED BELOWWET ABOVETMIN ABOVE ABOVETMED BELOWTMIN ODDSTMIN ODDSTMAX SPEARMANTMED ]
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	O=-0.25
max $partialdiff sub Y$ min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ] [ \| Y]	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
Differentiate along Y
Take differences along Y

max ∂Y min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ] : ∂Y Hecho en, Propensión - Precipitación data

Independent Variables (Grids)

Other Info

Data Views

Filters

max ∂_Y min [ S , min ( OLE2 CPT ESCENARIO1 PROPENSION ) ] : ∂_Y Hecho en, Propensión - Precipitación data