data: NextGen CPT Estacional CHIRPS Guatemala REALTIMEL4 Models COLA-RSMAS-CCSM4 History CrossValHind

NextGen CPT Estacional CHIRPS Guatemala REALTIMEL4 Models COLA-RSMAS-CCSM4 History CrossValHind: Procentaje de la mediana data

Procentaje de la mediana from NextGen CPT Estacional CHIRPS Guatemala REALTIMEL4 Models COLA-RSMAS-CCSM4 History: Predictand, Hindcast and Skill.

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
S: grid: /S (months since 1960-01-01) ordered (0000 1 Jan 1983) to (0000 1 Dec 2009) by 1.0 N= 324 pts :grid
Longitud (longitude): grid: /X (degree_east) ordered (92.5W) to (88W) by 0.1 N= 46 pts :grid
Latitud (latitude): grid: /Y (degree_north) ordered (13.5N) to (18.5N) by 0.1 N= 51 pts :grid

Other Info

CE: 16
colorscalename: precip_colors
CS: 0
datatype: realarraytype
maxncolor: 254
missing_value: -999.0
scale_max: 16.0
scale_min: 0.0
units: mm /dia
standard units*: mm /dia
colorscale

Last updated: Tue, 14 Feb 2023 21:52:41 GMT

Data Views

	L	S	X	Y
NextGen CPT Estacional CHIRPS Guatemala REALTIMEL4 Models COLA-RSMAS-CCSM4 History[CrossValHind InputObs hindcast_length hindcast_date ]
NextGen CPT Estacional CHIRPS Guatemala REALTIMEL4 Models COLA-RSMAS-CCSM4 History CrossValHind 2.5 months[ 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
Differentiate along S X Y
Take differences along S X Y