data: ALISIOS NextGen CHIRPS Seasonal OLE2 NASA-GEOSS2S Forecast PredErrorVars

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ALISIOS NextGen CHIRPS Seasonal OLE2 NASA-GEOSS2S Forecast PredErrorVars: prediction error variance data

prediction error variance from ALISIOS NextGen CHIRPS Seasonal OLE2 NASA-GEOSS2S 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
Longitud (longitude): grid: /X (degree_east) ordered (117.6837W) to (28.2837W) by 0.1 N= 895 pts :grid
Latitud (latitude): grid: /Y (degree_north) ordered (49.975S) to (32.6663N) by 0.10005 N= 827 pts :grid

Other Info

CE: null
colorscalename: rainbowcolorscale
CS: 0
datatype: realarraytype
maxncolor: 256
missing_value: -999.0
pointwidth: 0
scale_min: 0.0
units: mm² /day²
standard units*: 1.33959190672154×10^-16 meter² second^-2

Last updated: Tue, 07 Jan 2025 14:00:00 GMT

Data Views

	L	S	X	Y
ALISIOS NextGen CHIRPS Seasonal OLE2 NASA-GEOSS2S Forecast[target_date PredErrorVars PROBABILITIES PROB_FCST target_length Forecast ]
ALISIOS NextGen CHIRPS Seasonal OLE2 NASA-GEOSS2S Forecast PredErrorVars[ X Y \| S 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 X Y S L
Differentiate along X Y S L
Take differences along X Y S L