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∂Y root mean sq [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 History InputObs ] : ∂Y input observations data
InputObs InputObs ∂Y input observations from NextGen CPT 1p0 Guatemala NCEP-CFSv2 History: Predictand, Hindcast and Skill.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
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- realarraytype
- file_missing_value
- -999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- mm /dia /degree_north
- history
- Averaged over S[0000 1 Jan 1983, 0000 1 Dec 2009] minimum 0.0% data present
Last updated: Fri, 05 Nov 2021 18:02:01 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 | |
 $partialdiff sub Y$ root mean sq [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 History InputObs ] 2.5 months[ | X Y L] | M | M | M |
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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