data: NextGen CPT Estacional CHIRPS Guatemala V2 Models COLA-RSMAS-CCSM4 Forecast Mu

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NextGen CPT Estacional CHIRPS Guatemala V2 Models COLA-RSMAS-CCSM4 Forecast Mu: Pronóstico data

Pronóstico from NextGen CPT Estacional CHIRPS Guatemala V2 Models COLA-RSMAS-CCSM4 Forecast: Forecast and Error.

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
Hecho en (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jun 2021) to (0000 1 Nov 2021) by 1.0 N= 6 pts :grid
Longitud (longitude): grid: /X (degree_east) ordered (119.9W) to (70W) by 0.1 N= 500 pts :grid
Latitud (latitude): grid: /Y (degree_north) ordered (4.95S) to (39.95N) by 0.1 N= 450 pts :grid

Other Info

CE: 500
CS: 0
datatype: realarraytype
maxncolor: 254
missing_value: -999.0
scale_max: 500.0
scale_min: 0.0
units: mm /dia
standard units*: mm /dia
colorscale

Last updated: Thu, 17 Feb 2022 19:28:47 GMT

Data Views

	L	S	X	Y
NextGen CPT Estacional CHIRPS Guatemala V2 Models COLA-RSMAS-CCSM4 Forecast[PROB_FCST target_date target_length PredErrorVars Mu PROBABILITIES ]
NextGen CPT Estacional CHIRPS Guatemala V2 Models COLA-RSMAS-CCSM4 Forecast Mu 2.5 months[ 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
Differentiate along X Y S
Take differences along X Y S