data: mean min [ IRI Forecast_old SST_CFSV2-PRECIP

mean min [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History InputObs ] : input observations data

InputObs InputObs min input observations from IRI Forecast_old SST_CFSV2-PRECIP_GPCC History: Predicand, Hindcast and Skill.

Independent Variables (Grids)

L: grid: /L (months) ordered (2.0 months) to (3.0 months) N= 2 pts :grid
Forecast Issue Date (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2015) to (0000 1 Mar 2017) by 1.0 N= 27 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (29.5S) to (35.5S) by 1.0 N= 7 pts :grid

Other Info

bufferwordsize

CE

null

colorscalename

precip_colors

CS

null

datatype

doublearraytype

file_missing_value

-999.0

maxncolor

254

missing_value

NaN

pointwidth

3.0

units

mm /month

standard units*

0.012 meter year^-1

history

mean min [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History InputObs ]

min over T2[1982, 2013]
Averaged over X[60W, 52W] minimum 0.0% data present

Last updated: Wed, 08 Mar 2017 14:24:39 GMT

Data Views

	L	S	Y
mean min [ IRI Forecast_old SST_CFSV2-PRECIP_GPCC History InputObs ] [ Y \| S L]	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 Y S L
Differentiate along Y S L
Take differences along Y S L