data: mean root mean sq anom [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ]

mean root mean sq anom [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ] : Probabilidades data

PROBABILITIES PROBABILITIES Probabilidades from NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast: Forecast and Error.

Independent Variables (Grids)

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 Jan 2019) to (0000 1 Sep 2021) by 1.0 N= 33 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

history

[ dominant_class ( NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Sobre ) + masklt ( { [ dominant_class ( NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Normal ) + masknotrange ( { [ dominant_class ( NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ) - 1. ] * 11. } , 10 , 12 ) ]

dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Sobre ] + masklt [ ( { dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ] - 1. } * 11. ) , 22 ]

dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Sobre ]
dominant_class over PROB_FCST[≤35, ≥80]

masklt [ ( { dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo, Sobre]

dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Normal ] + masknotrange [ ( { dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ] - 1. } * 11. ) , 10 , 12 ]

dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Normal ]
dominant_class over PROB_FCST[≤35, ≥80]

masknotrange [ ( { dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo, Sobre]

dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Bajo ] + maskgt [ ( { dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ] - 1. } * 11. ) , 0 ]

dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Bajo ]
dominant_class over PROB_FCST[≤35, ≥80]

maskgt [ ( { dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo, Sobre]

root mean sq anom [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ]

Averaged over Y[12N, 19N] minimum 0.0% data present

mean root mean sq anom [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ]

Averaged over X[94.5W, 86.5W] minimum 0.0% data present

Last updated: Fri, 05 Nov 2021 18:02:01 GMT
Expires: Thu, 09 Dec 2021 00:00:00 GMT

Data Views

	L	S
mean root mean sq anom [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ] 2.5 months[ \| L S]	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
Differentiate along S
Take differences along S