data: $integral dS$ detrended-bfl [ ANACIM CPT ENACTSv1 cfs2 sst precip Forecast TercProb ]

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∫dS detrended-bfl [ ANACIM CPT ENACTSv1 cfs2 sst precip Forecast TercProb ] : Probabilités des Terciles data

TercProb adif Probabilités des Terciles from ANACIM CPT ENACTSv1 cfs2 sst precip Forecast: Prédictions.

Independent Variables (Grids)

Catégories de Terciles: grid: /C (ids) unordered [ (Sous_PNe) (Proche_PNe) (Audessus_PNe)] :grid
Horizon: grid: /L (months) ordered (2.5 months) to (4.5 months) N= 2 pts :grid
S (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 16 Mar 2018) to (0000 16 May 2018) by 1.0 N= 3 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (17.5875W) to (11.2125W) by 0.0375 N= 171 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (16.8N) to (12.225N) by 0.03749999 N= 123 pts :grid

Other Info

bufferwordsize: 8
CE: null
colorscalename: tercileclassesscale
CS: null
datatype: doublearraytype
file_missing_value: -1
maxncolor: 254
missing_value: NaN
pointwidth: 0
units: 0.000833333333333333 year

Last updated: Thu, 26 Oct 2023 14:58:08 GMT

Data Views

	C	L	S	X	Y
$integral dS$ detrended-bfl [ ANACIM CPT ENACTSv1 cfs2 sst precip Forecast TercProb ] [ X Y C \| L S]	M	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 C L S
Differentiate along X Y C L S
Take differences along X Y C L S