data: ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob

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ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob: Tercile Forecast data

Tercile Forecast from ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast: Forecast and Error.

Independent Variables (Grids)

Tercile Categories: grid: /C (ids) unordered [ (Below) (Normal) (Above)] :grid
Forecast Issue Date (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Feb 2021) to (0000 1 Jul 2022) by 1.0 N= 18 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (20.5E) to (53E) by 0.5 N= 66 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (13.5S) to (24.5N) by 0.5 N= 77 pts :grid

Other Info

bufferwordsize: 8
CE: 100
colorscalename: tercileclassesscale
CS: 0
datatype: doublearraytype
maxncolor: 254
missing_value: -1.0
pointwidth: 0
scale_max: 100.0
scale_min: 0.0
units: percent
standard units*: 0.01
colorscale

Last updated: Thu, 28 Jul 2022 20:33:36 GMT
Expires: Wed, 09 Jun 2021 00:00:00 GMT

Data Views

	C	S	X	Y
ICPAC Forecasts CPT Rainfallv2 Seasonal Forecast Prob[ 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