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mean mean [ ICPAC Forecasts CPT Rainfall Seasonal History PearsonR ] : Pearson correlation skill values data
PearsonR PearsonR Pearson correlation skill values from ICPAC Forecasts CPT Rainfall Seasonal History: Predictand, Hindcast and Skill. isIndependent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- correlationcolorscale
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -999.0
- maxncolor
- 254
- missing_value
- NaN
- units
- unitless
- history
- mean mean [ ICPAC Forecasts CPT Rainfall Seasonal History PearsonR ]
- Averaged over X[21.875E, 51.375E] S[0000 1 Jan, 0000 1 Dec] minimum 0.0% data present
Averaged over Y[11.625S, 23.125N] minimum 0.0% data present
- Averaged over X[21.875E, 51.375E] S[0000 1 Jan, 0000 1 Dec] minimum 0.0% data present
Last updated: Thu, 25 Feb 2021 08:46:12 GMT
Data Views
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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units