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root mean sq anom [ detrended-bfl ∫dT ∂T ( Indices nino EXTENDED NINO34 ) climatology ]: ∂T NINO34 data
EXTENDED NINO34 partial_T int_dT adif adif ∂T NINO34 from Indices nino: Indices representative of the NINO 3.4 region. isIndependent Variables (Grids)
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- sstacolorscale
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 1.00000002E30
- iridl:hasSemantics
- iridl:Nino3.4
- maxncolor
- 254
- units
- degree_Celsius
- standard units*
- degree_Kelvin
- history
- detrended-bfl $integral dT$ $partialdiff sub T$ [ Indices nino EXTENDED NINO34 ]
- OS extended by NCEP\0$G
$integral dY$ [ ( $integral dX$ { KAPLAN EXTENDED v2 ssta } { 120W - 170W } ) / ( $integral dX$ dataflag { KAPLAN EXTENDED v2 ssta } { 120W - 170W } ) ] [ 5N - 5S ]
detrended-bfl $integral dT$ $partialdiff sub T$ [ Indices nino EXTENDED NINO34 ] climatology- Averaged over T2[1856, 2013]
root mean sq anom [ detrended-bfl $integral dT$ $partialdiff sub T$ ( Indices nino EXTENDED NINO34 ) climatology ]- Averaged over T[Jan, Dec]
- OS extended by NCEP\0$G
References
Kaplan_etal1998Reynolds_etal2002
Last updated: Wed, 01 Feb 2023 14:07:40 GMT
Data Views
 Indices nino[EXTENDED
] |
 root mean sq anom [ detrended-bfl $integral dT$ $partialdiff sub T$ ( Indices nino EXTENDED NINO34 ) climatology ][ |] |
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