data: root mean sq anom root mean sq anom $integral dS$ [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]

served from 129.236.110.25

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

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

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
Latitude (latitude): grid: /Y (degree_north) ordered (50.25N) to (23.75N) by 0.5 N= 54 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 days

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 anom $integral dS$ [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]

Averaged over S[0000 17 Oct 2018, 0000 16 Dec 2018] minimum 0.0% data present

root mean sq anom root mean sq anom $integral dS$ [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]

Averaged over X[125.25W, 66.25W] minimum 0.0% data present

Last updated: Thu, 24 Jan 2019 03:12:42 GMT
Expires: Tue, 05 Feb 2019 00:00:00 GMT

Data Views

	L	Y
IRI NOAA-VECTOR R0FCST[PROBABILIDADES target_date R0FCST_DJF20182019 ]
root mean sq anom root mean sq anom $integral dS$ [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ] 2.5 months[ Y L \|]	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 Y
Differentiate along Y
Take differences along Y