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root mean sq ∫dS [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 History InputObs ] : input observations data
InputObs int_dS 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
- S
- grid: /S (months since 1960-01-01) ordered (0000 16 Dec 1982) to (0000 16 Dec 2009) by 1.0 N= 325 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (12N) to (19N) by 1.0 N= 8 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- mm /dia months
- history
- Averaged over X[94.5W, 86.5W] minimum 0.0% data present
Last updated: Fri, 05 Nov 2021 18:02:01 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| L | S | Y | |
 root mean sq $integral dS$ [ NextGen CPT 1p0 Guatemala NCEP-CFSv2 History InputObs ] 2.5 months[ S | 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 S Y
- Differentiate along S Y
- Take differences along S Y
RMS (root mean square with mean *not* removed) over S Y | S Y |
RMSA (root mean square with mean removed) over S Y | S Y |
Maximum over S Y | S Y |
Minimum over S Y | S Y |
Detrend (best-fit-line) over S Y | S Y |
Note on units