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ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS Forecast target_date: forecast time data
target_date forecast time from ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS 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
- S (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered [ (0000 1 Jan 2024) (0000 1 Feb 2024) (0000 1 Mar 2024) (0000 1 Apr 2024) (0000 1 May 2024) (0000 1 Jun 2024) (0000 1 Jul 2024) (0000 1 Aug 2024) (0000 1 Sep 2024) (0000 1 Oct 2024) (0000 1 Nov 2024) (0000 1 Dec 2024) (0000 1 Jan 2025)] :grid
Other Info
- calendar
- 360
- CE
- null
- CS
- null
- datatype
- realarraytype
- gridid
- 191587160
- pointwidth
- 3
- scale_max
- null
- scale_min
- null
- standard_name
- forecast_reference_time
- units
- months since 1960-01-01
- standard units*
- 0.0833333333333333 ( years since 1960-01-01 00:00.000000000 )
Last updated: Wed, 15 Jan 2025 19:24:21 GMT
Expires: Sun, 09 Feb 2025 00:00:00 GMT
Data Views
Views
data as colors
data as contours
line plots
color bars| L | S | |
 ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS[History
Forecast
Skill
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 ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS Forecast target_date[ 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