served from 45.183.221.150
max ∂Y [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ] : ∂Y Probabilidades data
PROBABILITIES partial_Y ∂Y 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
- Longitud (longitude)
- grid: /X (degree_east) ordered (94W) to (87W) by 1.0 N= 8 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (12.5N) to (18.5N) by 1.0 N= 7 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 33
- colorscalename
- halfgreyscale
- CS
- 1
- datatype
- realarraytype
- file_missing_value
- 0
- fnname
- maskle
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- ids /degree_north
- 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 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 Normal ]
- 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 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]
- dominant_class [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 Forecast PROB_FCST Bajo ]
- max over S[0000 1 Jan 2019, 0000 1 Sep 2021]
- [ 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 ) ]
- colorscale
Last updated: Fri, 05 Nov 2021 18:02:01 GMT
Expires: Thu, 09 Dec 2021 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts
line plots
color bars| L | X | Y | |
 max $partialdiff sub Y$ [ NextGen CPT Estacional CPC Guatemala NCEP-CFSv2-PY Forecast PROBABILITIES ] 2.5 months[ X Y | L] | 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 Y
- Differentiate along X Y
- Take differences along X Y
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |
Note on units