data: $partialdiff sub S$ root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ]

served from 129.236.110.25

∂_S root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ] : ∂_S Hecho en, Probabilidades -Días Lluviosos data

∂_S root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ] .

Independent Variables (Grids)

S (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (Jan 2000) to (Nov 2025) by 1.0 N= 311 pts :grid

Other Info

CE

null

CS

null

datatype

realarraytype

fnname

min

gridid

175490080

missing_value

NaN

pointwidth

scale_max

null

scale_min

null

standard_name

forecast_reference_time

units

unitless

history

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

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

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

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

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

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

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

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

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

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

min [ OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ]

min over S[0000 1 Jan 2000, 0000 1 Dec 2025]

$partialdiff sub S$ root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ]

Averaged over X[117.75W, 28.25W] Y[32.75N, 62.75S] minimum 0.0% data present

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[SPEARMANTMIN BELOWTMED BELOWWET PROPENSIONTMED ODDS ODDSWETDAYS ABOVETMIN ABOVE AFCTMED BELOWTMIN ODDSTMIN ODDSTMAX SPEARMANTMED PROPENSIONTMIN PROBABILIDADES PROPENSION PROBABILIDADESTMED TMED BELOW ABOVETMAX PROBABILIDADESWETDAYS SPEARMAN AFCTMIN TMIN BELOWTMAX SPEARMANTMAX PRECIPITACION PROPENSIONTMAX SPEARMANWET AFC ODDSTMED WETDAY PROBABILIDADESTMIN ABOVEWET AFCTMAX PROPENSIONWETDAYS target_date AFCWET ABOVETMED TMAX PROBABILIDADESTMAX ]
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
$partialdiff sub S$ root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ] [ 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

∂S root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ] : ∂S Hecho en, Probabilidades -Días Lluviosos data

Independent Variables (Grids)

Other Info

Data Views

Filters

∂_S root mean sq anom min [ S , min ( OLE2 CPT ESCENARIO1 PROBABILIDADESWETDAYS ) ] : ∂_S Hecho en, Probabilidades -Días Lluviosos data