data: root mean sq anom min [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]

served from 129.236.110.25

root mean sq anom min [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ] : Probabilidades -Días Lluviosos data

root mean sq anom min [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ] .

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
Hecho en (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 Mar 2025) by 1.0 N= 303 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 ESCENARIO2 WETDAY Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY ) - 1. ] * 11. } , 10 , 12 ) ]

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

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

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

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

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

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

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

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

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

min [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]

min over X[117.5W, 28.5W]

root mean sq anom min [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]

Averaged over Y[32.75N, 62.75S] 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

	C	L	S	X	Y
OLE2 CPT ESCENARIO2[PRECIPITACION BELOWTMED SPEARMANWET ODDSTMED PROBABILIDADESWETDAYS AFCTMED target_date AFCTMAX PROBABILIDADESTMIN ABOVEWET TMAX PROBABILIDADESTMAX ODDSWETDAYS AFCWET PROPENSIONWETDAYS SPEARMAN PROPENSIONTMED SPEARMANTMIN BELOWWET ABOVETMAX ABOVETMIN ABOVE BELOWTMAX ODDS ODDSTMAX ODDSTMIN AFC BELOWTMIN SPEARMANTMED PROPENSION TMED PROBABILIDADESTMED PROPENSIONTMIN SPEARMANTMAX TMIN PROBABILIDADES BELOW ABOVETMED WETDAY AFCTMIN PROPENSIONTMAX ]
OLE2 CPT ESCENARIO2 ODDSTMED 2.5 months[ X Y C \| S L]	M	M	M	M	M
root mean sq anom min [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ] 2.5 months[ \| L S]		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 S
Differentiate along S
Take differences along S