served from IRI/LDEO Climate Data Library
detrended-bfl [ IGOSS TOGA-TAO.cdf sst ]: sea surface temperature data
sst sst sea surface temperature from IGOSS TOGA-TAO.cdf: Wind vectors and sea surface temperatures from the TOGA-TAO array in the tropical Pacific.Independent Variables (Grids)
- depth
- grid: /depth (m) ordered [ (0.0)] :grid
- time
- grid: /time (months since 1960-01-01) ordered (Jan 1991) to (Oct 2014) by 1.0 N= 286 pts :grid
- Longitude
- grid: /X (degree_east) ordered (130E) to (95W) by 1.0 N= 136 pts :grid
- Latitude
- grid: /Y (degree_north) ordered (9S) to (12N) by 1.0 N= 22 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CI
- 0.5
- colorscalename
- sstcolorscale
- CS
- null
- datatype
- doublearraytype
- epic_code
- 20
- file_missing_value
- 1.00000004E35
- FORTRAN_format
- f10.2
- generic_name
- temp
- missing_value
- NaN
- units
- C
- standard units*
- ampere second
- history
- [(Mean surface wind vectors (m/s) and sea surface temperature (C) as well as anomalies in the tropical Pacific.) (COADS Wind and Reynold-Smith (1994) climatologies.) (USA-FRANCE-JAPAN-KOREA-TAIWAN)]
References
Mangum,L.J., H.P. Freitag, and M.J. McPhaden.TOGA-TAO Array Sampling Schemes and Sensor Evaluations. Proceedings of the Oceans '94 OSATES, Brest, France, 13-16 September 1994, Vol II, pp. 402-406.Soreide, N.N., D.C. McClurg, W.H. Zhu, M.J. McPhaden, L.J. Mangum, and D.W. Denbo, Distribution and Display of TOGA-TAO Buoy Data, Proceedings of Oceans 94, OSATES, Brest, France, 13-16 September 1994, Vol II
Last updated: Wed, 13 Feb 2019 20:27:28 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| depth | time | X | Y | |
 detrended-bfl [ IGOSS TOGA-TAO.cdf sst ] 0.0 m[ X Y depth | time] | M | M | M | 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 X Y time
- Differentiate along X Y time
- Take differences along X Y time
RMS (root mean square with mean *not* removed) over X Y time | X Y X time Y time | X Y time |
RMSA (root mean square with mean removed) over X Y time | X Y X time Y time | X Y time |
Maximum over X Y time | X Y X time Y time | X Y time |
Minimum over X Y time | X Y X time Y time | X Y time |
Detrend (best-fit-line) over X Y time | X Y X time Y time | X Y time |
Note on units