data: min [ S , root mean sq anom min ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ]

served from 129.236.110.25

min [ S , root mean sq anom min ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ]: Hecho en, Probabilidades -Temperatura Mínima data

min [ S , root mean sq anom min ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ].

Independent Variables (Grids)

S (forecast_reference_time): grid: /S (days since 1960-01-01) ordered [ (0000 1 Jan 2000) (0000 1 Feb 2000) (0000 1 Mar 2000) ... (0000 1 Dec 2025)] N= 312 pts :grid
Latitud (latitude): grid: /Y (degree_north) ordered (32.75N) to (62.75S) by 0.5 N= 192 pts :grid

Other Info

calendar

360

datatype

realarraytype

fnname

min

gridid

175456864

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 ESCENARIO2 TMIN Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO2 TMIN ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO2 TMIN Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO2 TMIN ) - 1. ] * 11. } , 10 , 12 ) ]

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

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

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

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

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

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

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

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

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

min [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ]

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

root mean sq anom min [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ]

Averaged over X[117.75W, 28.25W] 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	Y
OLE2 CPT ESCENARIO2[SPEARMANTMAX BELOWTMED ABOVETMAX PROPENSIONTMIN ODDSTMIN BELOWTMAX ODDSTMAX SPEARMANTMED PROBABILIDADES PROPENSION PROBABILIDADESTMED TMED ABOVETMED PROBABILIDADESWETDAYS TMIN target_date ABOVE SPEARMANTMIN PROBABILIDADESTMIN PROPENSIONWETDAYS AFCTMIN PROPENSIONTMAX BELOW ODDS ODDSTMED WETDAY ODDSWETDAYS SPEARMANWET AFC AFCTMED AFCWET ABOVETMIN SPEARMAN PRECIPITACION PROBABILIDADESTMAX TMAX BELOWTMIN ABOVEWET BELOWWET PROPENSIONTMED AFCTMAX ]
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		M
min [ S , root mean sq anom min ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ][ \| 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