data: IRI CPT SONDv5 total_rainfall Forecast TercProb

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IRI CPT SONDv5 total_rainfall Forecast TercProb: Tercile Probabilities data

Tercile Probabilities from IRI CPT SONDv5 total_rainfall Forecast: Forecast and Error.

Independent Variables (Grids)

Tercile Categories: grid: /C (ids) unordered [ (Below_Normal) (Near_Normal) (Above_Normal)] :grid
Start time (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Aug 2015) to (0000 1 Aug 2018) by 12.0 N= 4 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (28.5375E) to (30.975E) by 0.0375 N= 66 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (2.9625S) to (1.05S) by 0.0375 N= 52 pts :grid

Other Info

CE: 100
colorscalename: tercileclassesscale
CS: 0
datatype: realarraytype
file_missing_value: -999.0
maxncolor: 254
missing_value: NaN
pointwidth: 0
scale_max: 100.0
scale_min: 0.0
units: percent
standard units*: 0.01
history: percentiles computed over S:Aug 1982 - Jul 2017 0% min data present
colorscale

Last updated: Wed, 11 Dec 2019 13:31:54 GMT
Expires: Sat, 01 Aug 2020 00:00:00 GMT

Data Views

	C	S	X	Y
IRI CPT SONDv5 total_rainfall Forecast TercProb[ X Y \| C S]	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 S
Differentiate along X Y C S
Take differences along X Y C S