served from 129.236.110.25
max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ]: Hecho en, Probabilidades -Temperatura Mínima data
max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ].Independent Variables (Grids)
- Hecho en (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 Dec 2025) by 1.0 N= 312 pts :grid
- Longitud (longitude)
- grid: /X (degree_east) ordered (117.75W) to (28.25W) by 0.5 N= 180 pts :grid
Other Info
- calendar
- 360
- datatype
- realarraytype
- fnname
- max
- gridid
- 175490048
- missing_value
- NaN
- pointwidth
- 0
- 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 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 Normal ]
- 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 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]
- dominant_class [ OLE2 CPT ESCENARIO2 TMIN Bajo la Normal ]
- Averaged over S[0000 1 Jan 2000, 0000 1 Dec 2025] minimum 0.0% data present
max root mean sq anom [ OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ]- max over Y[32.75N, 62.75S]
- [ 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 ) ]
Last updated: Sat, 06 Dec 2025 07:30:02 GMT
Expires: Mon, 05 Jan 2026 00:00:00 GMT
Data Views
Views
data as colors
data as contours| S | X | |
 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 | M | |
|---|---|---|
| grid: /Y (degree_north) ordered (32.75N) to (62.75S) by 0.5 N= 192 pts :grid | ||
 max [ S , max root mean sq anom ( OLE2 CPT ESCENARIO2 PROBABILIDADESTMIN ) ][ | S X] | 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 X
- Differentiate along S X
- Take differences along S X
RMS (root mean square with mean *not* removed) over S X | S X |
RMSA (root mean square with mean removed) over S X | S X |
Maximum over S X | S X |
Minimum over S X | S X |
Detrend (best-fit-line) over S X | S X |
Note on units