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ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 Forecast target_length: Length of forecast time data
Length of forecast time from ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 Forecast: Forecast and Error.Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered (2.5 months) to (4.5 months) by 1.0 N= 3 pts :grid
- Hecho en (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2024) to (0000 1 Dec 2024) by 1.0 N= 12 pts :grid
Other Info
- calendar
- 360
- CE
- null
- CS
- null
- datatype
- realarraytype
- missing_value
- NaN
- pointwidth
- 1.0
- units
- days
- standard units*
- 86400 second
- history
- Averaged in T with overlapping interval 3
Last updated: Tue, 07 Jan 2025 14:00:00 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| L | S | |
 ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1[Forecast
Skill
History
] | ||
 ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 Forecast target_length[ S L |] | 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 L
- Differentiate along S L
- Take differences along S L
RMS (root mean square with mean *not* removed) over S L | S L |
RMSA (root mean square with mean removed) over S L | S L |
Maximum over S L | S L |
Minimum over S L | S L |
Detrend (best-fit-line) over S L | S L |
Note on units