data: $integral dX$ $partialdiff sub L$ [ IRI FD Seasonal

served from IRI/LDEO Climate Data Library

∫dX ∂_L [ IRI FD Seasonal_Forecast Precipitation prob ] : ∂_L Tercile Probability data

Precipitation prob partial_L ∂_L 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
Month Forecast Issued: grid: /F (months since 1960-01-01) ordered [ (Sep 1997) (Dec 1997) (Mar 1998) ... (Mar 2017)] N= 205 pts :grid
L: grid: /L (months) ordered (1.5 months) to (3.5 months) by 1.0 N= 3 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (180W) to (180) by 2.5 N= 145 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (88.75N) to (88.75S) by 2.5 N= 72 pts :grid

Other Info

bufferwordsize: 8
CE: 100
colorscalename: tercileclassesscale
CS: 0
datatype: doublearraytype
file_missing_value: -9.0
maxncolor: 254
missing_value: NaN
units: 0.0020943951023932 radian east year^-1
colorscale

References

Barnston_etal2003

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

Data Views

	C	F	L	X	Y
$integral dX$ $partialdiff sub L$ [ 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