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min ∂X ∫dY [ KAPLAN EXTENDED v2 ssta ] : ∂X SST anomaly\0~ data
ssta int_dY partial_X min ∂X SST anomaly\0~ from KAPLAN EXTENDED v2: Statistically homogenous concatenation of Kaplan et al [1998] OS SST and Reynolds and Smith [1994] NCEP OI analyses; the latter gets degraded to the resolution of the former\0 àÝX .Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) ordered [ (Jan 1856) (Feb 1856) (Mar 1856) ... (Jul 2014)] N= 1903 pts :grid
- Latitude
- grid: /Y (degree_north) ordered (90S) to (90N) by 5.0 N= 37 pts :grid
Other Info
- datatype
- realarraytype
- file_missing_value
- 1.00000002E30
- missing_value
- NaN
- units
- degree_Celsius
- standard units*
- degree_Kelvin
- history
- min $partialdiff sub X$ $integral dY$ [ KAPLAN EXTENDED v2 ssta ]
- OS extended by NCEP\0$G
min over X[25E, 20E]
- OS extended by NCEP\0$G
References
Kaplan, A., M. Cane, Y. Kushnir, A. Clement, M. Blumenthal, and B. Rajagopalan, Analyses of global sea surface temperature 1856-1991, Journal of Geophysical Research, 103, 18,567-18,589, 1998R. W. Reynolds, T. M. Smith. Improved global sea surface temperature analyses.. J. Climate 7, 1994
Last updated: Tue, 29 Mar 2016 08:02:46 GMT
Data Views
Views
data as colors
data as contours
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 Y T
- Differentiate along Y T
- Take differences along Y T
RMS (root mean square with mean *not* removed) over Y T | Y T |
RMSA (root mean square with mean removed) over Y T | Y T |
Maximum over Y T | Y T |
Minimum over Y T | Y T |
Detrend (best-fit-line) over Y T | Y T |
Note on units