data: $integral dS$ max [ S , max $integral dY$ ( OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ) ]

served from 129.236.110.25

∫dS max [ S , max ∫dY ( OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ) ] : Hecho en, Probabilidades -Días Lluviosos data

∫dS max [ S , max ∫dY ( OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ) ] .

Independent Variables (Grids)

S (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 16 Dec 1999) to (0000 16 Dec 2025) by 1.0 N= 313 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (33N) to (63S) by 0.5 N= 193 pts :grid

Other Info

bufferwordsize

calendar

360

CE

null

CS

null

datatype

doublearraytype

fnname

max

gridid

175490048

missing_value

NaN

pointwidth

scale_max

null

scale_min

null

standard_name

forecast_reference_time

units

0.00694444444444444 ( year above 2000 ) year

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]

max $integral dY$ [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]

max over X[117.75W, 28.25W]

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

Data Views

	S	Y
OLE2 CPT ESCENARIO2[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
$integral dS$ max [ S , max $integral dY$ ( OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ) ] [ \| S Y]	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 Y
Differentiate along S Y
Take differences along S Y

Average over S Y | S Y |
RMS (root mean square with mean *not* removed) over S Y | S Y |
RMSA (root mean square with mean removed) over S Y | S Y |
Maximum over S Y | S Y |
Minimum over S Y | S Y |
Detrend (best-fit-line) over S Y | S Y |

Note on units