data: max [ S , max $integral dY$ ( IRI NOAA-VECTOR R0FCST PROBABILIDADES ) ]

served from 129.236.110.25

max [ S , max ∫dY ( IRI NOAA-VECTOR R0FCST PROBABILIDADES ) ]: Hecho en, Probabilities data

max [ S , max ∫dY ( IRI NOAA-VECTOR R0FCST PROBABILIDADES ) ].

Independent Variables (Grids)

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

Other Info

calendar

360

datatype

realarraytype

fnname

max

gridid

175954720

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 ( 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]

max $integral dY$ [ IRI NOAA-VECTOR R0FCST PROBABILIDADES ]

max over Y[50.5N, 23.5N]

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

Data Views

	S	X
IRI NOAA-VECTOR R0FCST[R0FCST_DJF20182019 PROBABILIDADES target_date ]
grid: /X (degree_east) ordered (125.25W) to (66.25W) by 0.5 N= 119 pts :grid		M
grid: /Y (degree_north) ordered (50.25N) to (23.75N) by 0.5 N= 54 pts :grid
max [ S , max $integral dY$ ( IRI NOAA-VECTOR R0FCST PROBABILIDADES ) ][ \| 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

Average over S X | 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