data: $partialdiff sub F$ $partialdiff sub F$ [ IRI FD Seasonal

served from IRI/LDEO Climate Data Library

∂_F ∂_F [ IRI FD Seasonal_Forecast Precipitation prob ] : ∂_F ∂_F Tercile Probability data

Precipitation prob partial_F ∂_F ∂_F Tercile Probability from IRI FD Seasonal_Forecast: Seasonal forecasts for probabilities of below-normal, above-normal, and extreme precipitation and temperature.

Independent Variables (Grids)

Tercile Classes: grid: /C (ids) unordered [ (Below_Normal) (Normal) (Above_Normal)] :grid
F: grid: /F (months since 1960-01-01) ordered [ (Nov 1997 - Jan 1998) (Feb-Apr 1998) (May-Jul 1998) ... (Feb 2017)] N= 203 pts :grid
Forecast Lead Time in Months: grid: /L (months) ordered (1.0 months) to (4.0 months) by 1.0 N= 4 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (178.75W) to (178.75E) by 2.5 N= 144 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (88.75N) to (88.75S) by 2.5 N= 72 pts :grid

Other Info

CE: 100
colorscalename: tercileclassesscale
CS: 0
datatype: realarraytype
file_missing_value: -9.0
maxncolor: 254
missing_value: NaN
units: 1.44 year^-2
colorscale

References

Barnston_etal2003

Last updated: Tue, 23 Nov 2021 19:15:25 GMT

Data Views

	C	F	L	X	Y
$partialdiff sub F$ $partialdiff sub F$ [ IRI FD Seasonal_Forecast Precipitation prob ] [ C X Y \| L F]	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 C X Y L F
Differentiate along C X Y L F
Take differences along C X Y L F