data: NextGen CPT 1p0 Guatemala NCEP-CFSv2-PY Forecast target

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NextGen CPT 1p0 Guatemala NCEP-CFSv2-PY Forecast target_date: forecast time data

target_date forecast time from NextGen CPT 1p0 Guatemala NCEP-CFSv2-PY Forecast: Forecast and Error.

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
S (forecast_reference_time): grid: /S (days since 1960-01-01) ordered [ (0000 1 Jan 2019) (0000 1 Feb 2019) (0000 1 Mar 2019) (0000 1 Apr 2019) (0000 1 May 2019) (0000 1 Jun 2019) (0000 1 Jul 2019) (0000 1 Aug 2019) (0000 1 Sep 2019) (0000 1 Oct 2019) (0000 1 Nov 2019) (0000 1 Dec 2019) (0000 1 Jan 2020) (0000 1 Feb 2020) (0000 1 Mar 2020) (0000 1 Apr 2020) (0000 1 May 2020) (0000 1 Jun 2020) (0000 1 Jul 2020) (0000 1 Aug 2020) (0000 1 Sep 2020) (0000 1 Oct 2020) (0000 1 Nov 2020) (0000 1 Dec 2020) (0000 1 Jan 2021) (0000 1 Feb 2021) (0000 1 Mar 2021) (0000 1 Apr 2021) (0000 1 May 2021) (0000 1 Jun 2021) (0000 1 Jul 2021) (0000 1 Aug 2021) (0000 1 Sep 2021) (0000 1 Oct 2021) (0000 1 Nov 2021)] :grid

Other Info

calendar: 360
CE: null
CS: null
datatype: realarraytype
gridid: 173087552
pointwidth: 3
scale_max: null
scale_min: null
standard_name: forecast_reference_time
units: months since 1960-01-01
standard units*: 0.0833333333333333 ( years since 1960-01-01 00:00.000000000 )

Last updated: Wed, 24 Nov 2021 15:09:47 GMT
Expires: Wed, 09 Sep 2020 00:00:00 GMT

Data Views

	L	S
NextGen CPT 1p0 Guatemala NCEP-CFSv2-PY Forecast target_date 2.5 months[ S L \|]	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
Differentiate along S
Take differences along S