data: Indices nino NCEP NINO4

served from IRI/LDEO Climate Data Library

Indices nino NCEP NINO4: NINO4 data

NCEP NINO4 from Indices nino: Indices representative of the NINO 1 and 2, NINO 3, NINO 3.4, and NINO 4 regions.

Independent Variables (Grids)

Time (time): grid: /T (months since 1960-01-01) ordered (Nov 1981) to (Mar 2003) by 1.0 N= 257 pts :grid

Other Info

bufferwordsize

CE

4.1999998

colorscalename

sstacolorscale

CS

-4.1999998

datatype

doublearraytype

iridl:hasSemantics

iridl:Nino4

maxncolor

254

PLOTCOAST

scale_max

4.1999998

scale_min

-4.1999998

units

degree_Celsius

standard units*

degree_Kelvin

history

$integral dY$ [ $integral dX$ ( NOAA NCEP EMC CMB GLOBAL Reyn_SmithOIv1 monthly ssta ) ( 150W - 160E ) ] [ 5N - 5S ]

$integral dX$ [ NOAA NCEP EMC CMB GLOBAL Reyn_SmithOIv1 monthly ssta ]

Monthly mean sea surface temperature anomaly (blended from ship, buoy, and bias-corrected satellite data)

$integral dY$ [ $integral dX$ dataflag ( NOAA NCEP EMC CMB GLOBAL Reyn_SmithOIv1 monthly ssta ) ( 150W - 160E ) ] [ 5N - 5S ]

NOAA NCEP EMC CMB GLOBAL Reyn_SmithOIv1 monthly ssta

Monthly mean sea surface temperature anomaly (blended from ship, buoy, and bias-corrected satellite data)

Indices nino NCEP NINO4

$integral dY$ [ ( $integral dX$ { NOAA NCEP EMC CMB GLOBAL Reyn_SmithOIv1 monthly ssta } { 150W - 160E } ) / ( $integral dX$ dataflag { NOAA NCEP EMC CMB GLOBAL Reyn_SmithOIv1 monthly ssta } { 150W - 160E } ) ] [ 5N - 5S ]

colorscale

References

R. W. Reynolds, T. M. Smith. Improved global sea surface temperature analyses.. J. Climate 7, 1994

Last updated: Mon, 18 Dec 2023 16:14:30 GMT

Data Views

	T
Indices nino NCEP NINO4[ \| T]	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 T
Differentiate along T
Take differences along T