data: ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 History InputObs

ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 History InputObs: Observaciones data

InputObs Observaciones from ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 History: Predictand, Hindcast and Skill.

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: grid: /S (days since 1960-01-01) ordered [ (0000 1 Jan 1991) (0000 1 Feb 1991) (0000 1 Mar 1991) ... (0000 1 Dec 2020)] N= 360 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 (32.6663N) to (49.975S) by 0.10005 N= 827 pts :grid

Other Info

CE: null
colorscalename: precip_colors
CS: 0
datatype: realarraytype
maxncolor: 254
missing_value: -999.0
pointwidth: 0
scale_min: 0.0
units: mm
standard units*: 0.001 meter

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

Data Views

	L	S	X	Y
ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1[History Skill Forecast ]
ALISIOS NextGen CHIRPS Seasonal OLE2 COLA-RSMAS-CESM1 History InputObs[ S \| X Y 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 S X Y L
Differentiate along S X Y L
Take differences along S X Y L