data: ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS Forecast target

served from 129.236.110.25

ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS Forecast target_date: forecast time data

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
Hecho en (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2024) to (0000 1 Jan 2025) by 1.0 N= 13 pts :grid

Other Info

calendar: 360
CE: null
CS: null
datatype: realarraytype
gridid: 190638256
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: Tue, 07 Jan 2025 14:00:00 GMT

Data Views

	L	S
ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS Forecast[PredErrorVars PROB_FCST PROBABILITIES target_length Forecast target_date ]
grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2024) to (0000 1 Jan 2025) by 1.0 N= 13 pts :grid		M
grid: /L (months) ordered (2.5 months) to (4.5 months) by 1.0 N= 3 pts :grid	M
ALISIOS NextGen CHIRPS Seasonal OLE2 ECC-CanSIPS Forecast target_date[ S L \|]	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 L
Differentiate along S L
Take differences along S L

Average over S L | 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