data: $partialdiff sub C$ [ IRI FD Seasonal_Forecast Extreme

served from IRI/LDEO Climate Data Library

∂_C [ IRI FD Seasonal_Forecast Extreme_Precipitation prob ]: ∂_C Tercile Probability data

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

Independent Variables (Grids)

C: grid: /C (ids) unordered [ () (8��)] :grid
Month Forecast Issued: grid: /F (months since 1960-01-01) ordered [ (Mar 1998) (Jun 1998) (Sep 1998) ... (Mar 2017)] N= 203 pts :grid
Forecast Lead Time in Months: grid: /L (months) ordered [ (1)] :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

datatype: realarraytype
file_missing_value: -9.0
missing_value: NaN
units: unitless /ids

References

Barnston, A.G., S.J. Mason, L. Goddard, D.G. DeWitt, S.E. Zebiak. 2003. Multimodel Ensembling in Seasonal Climate Forecasting at IRI. Bull. Amer. Met. Soc. 84 (12): 1783-1796.

Barnston_Mason2011

Last updated: Tue, 23 Nov 2021 19:16:14 GMT

Data Views

	C	F	L	X	Y
$partialdiff sub C$ [ IRI FD Seasonal_Forecast Extreme_Precipitation prob ] 1 months[ 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 F
Differentiate along C X Y F
Take differences along C X Y F