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NextGen CPT 0p1 Guatemala V1 Models COLA-RSMAS-CCSM4 Skill ROCAbove: ROC Above - CCA Deterministic Hindcasts data
ROC Above - CCA Deterministic Hindcasts from NextGen CPT 0p1 Guatemala V1 Models COLA-RSMAS-CCSM4 Skill: Forecast Skills.Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- S
- grid: /S (months since 01-Jan) periodic (Jan) to (Dec) by 1.0 N= 12 pts :grid
- Longitud (longitude)
- grid: /X (degree_east) ordered (119.9W) to (70W) by 0.1 N= 500 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (39.95N) to (4.95S) by 0.1 N= 450 pts :grid
Other Info
- CE
- 100.0
- colorscalename
- correlationcolorscale
- CS
- 0.0
- datatype
- realarraytype
- file_missing_value
- -999
- maxncolor
- 254
- missing_value
- NaN
- scale_max
- 100.0
- scale_min
- 0.0
- colorscale
Last updated: Thu, 17 Feb 2022 19:19:15 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 0p1 Guatemala V1 Models COLA-RSMAS-CCSM4 Skill ROCAbove 2.5 months[ X Y | S L] | M | 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 S
- Differentiate along X Y S
- Take differences along X Y S
RMS (root mean square with mean *not* removed) over X Y S | X Y X S Y S | X Y S |
RMSA (root mean square with mean removed) over X Y S | X Y X S Y S | X Y S |
Maximum over X Y S | X Y X S Y S | X Y S |
Minimum over X Y S | X Y X S Y S | X Y S |
Detrend (best-fit-line) over X Y S | X Y X S Y S | X Y S |
Note on units