data: min $integral dS$ detrended-bfl [ ICPAC Forecasts CPT Rainfall Seasonal History PearsonR ]

min ∫dS detrended-bfl [ ICPAC Forecasts CPT Rainfall Seasonal History PearsonR ] : Pearson correlation skill values data

PearsonR adif int_dS Pearson correlation skill values from ICPAC Forecasts CPT Rainfall Seasonal History: Predictand, Hindcast and Skill. is

Independent 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: months
standard units*: 0.0833333333333333 year
history: min over X[22E, 51.25E] Y[11.5S, 23N] S[0000 16 Dec 1959, 0000 16 Dec 1960]

Last updated: Thu, 25 Feb 2021 08:46:12 GMT

Data Views

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min $integral dS$ detrended-bfl [ ICPAC Forecasts CPT Rainfall Seasonal History PearsonR ] 2.5 months[ \| L]	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
Differentiate along
Take differences along

Average over
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