data: root mean sq [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]

servi depuis 129.236.110.25

root mean sq [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]: Probabilities data

root mean sq [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ].

Variables Indépendantes (Grilles)

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 Nov 2018) to (0000 1 Dec 2018) N= 2 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (125.25W) to (66.25W) by 0.5 N= 119 pts :grid

Autres Informations

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 ( IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Above ) + masklt ( { [ dominant_class ( IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Normal ) + masknotrange ( { [ dominant_class ( IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ) - 1. ] * 11. } , 10 , 12 ) ]

dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Above ] + masklt [ ( { dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ] - 1. } * 11. ) , 22 ]

dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Above ]
dominant_class over R0FCST_DJF20182019[<35, >80]

masklt [ ( { dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ] - 1. } * 11. ) , 22 ]
dominant_class over C[Below, Above]

dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Normal ] + masknotrange [ ( { dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ] - 1. } * 11. ) , 10 , 12 ]

dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Normal ]
dominant_class over R0FCST_DJF20182019[<35, >80]

masknotrange [ ( { dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Below, Above]

dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Below ] + maskgt [ ( { dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ] - 1. } * 11. ) , 0 ]

dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 Below ]
dominant_class over R0FCST_DJF20182019[<35, >80]

maskgt [ ( { dominant_class [ IRI NOAA-VECTOR R0FCST R0FCST_DJF20182019 ] - 1. } * 11. ) , 0 ]
dominant_class over C[Below, Above]

root mean sq [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]

Averaged over Y[23.75N, 50.25N] minimum 0.0% data present

Dernière Mise à jour: Thu, 24 Jan 2019 03:12:42 GMT
Expire: Tue, 05 Feb 2019 00:00:00 GMT

Data Views

	L	S	X
root mean sq [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ] 2.5 months[ X \| L S]	M	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 X S
Differentiate along X S
Take differences along X S

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

Note on units