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NextGen CPT Estacional CPC Guatemala GFDL-CM2p5-FLOR-B01 History InputObs: input observations data
input observations from NextGen CPT Estacional CPC Guatemala GFDL-CM2p5-FLOR-B01 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 1 Jan 1983) to (0000 1 Dec 2009) by 1.0 N= 324 pts :grid
- Longitud (longitude)
- grid: /X (degree_east) ordered (94W) to (87W) by 1.0 N= 8 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (12N) to (19N) by 1.0 N= 8 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- null
- colorscalename
- precip_colors
- CS
- 0
- datatype
- realarraytype
- maxncolor
- 254
- missing_value
- -999.0
- pointwidth
- 0
- scale_min
- 0.0
- units
- mm /dia
- standard units*
- mm /dia
Last updated: Fri, 10 Apr 2020 20:38:42 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | S | X | Y | |
 NextGen CPT Estacional CPC Guatemala GFDL-CM2p5-FLOR-B01 History[CrossValHind
hindcast_length
InputObs
hindcast_date
] | ||||
| grid: /S (months since 1960-01-01) ordered (0000 1 Jan 1983) to (0000 1 Dec 2009) by 1.0 N= 324 pts :grid | M | |||
|---|---|---|---|---|
| grid: /X (degree_east) ordered (94W) to (87W) by 1.0 N= 8 pts :grid | M | |||
| grid: /Y (degree_north) ordered (12N) to (19N) by 1.0 N= 8 pts :grid | M | |||
| NextGen CPT Estacional CPC Guatemala GFDL-CM2p5-FLOR-B01 History InputObs 2.5 months[ S | X Y L] | M | M | M | M |
 NextGen CPT Estacional CPC Guatemala GFDL-CM2p5-FLOR-B01 History InputObs 2.5 months[ S | X Y L] | M | 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 S X Y
- Differentiate along S X Y
- Take differences along S X Y
RMS (root mean square with mean *not* removed) over S X Y | S X S Y X Y | S X Y |
RMSA (root mean square with mean removed) over S X Y | S X S Y X Y | S X Y |
Maximum over S X Y | S X S Y X Y | S X Y |
Minimum over S X Y | S X S Y X Y | S X Y |
Detrend (best-fit-line) over S X Y | S X S Y X Y | S X Y |
Note on units