served from IRI/LDEO Climate Data Library
∂X ∫dX ∫dT ∂T [ IGOSS ers1 sealevel ] : ∂X ∂T Sea Level Anomaly data
sealevel partial_T int_dT int_dX int_dX ∂X ∂T Sea Level Anomaly from IGOSS ers1: Analysis of monthly mean ERS-1 altimeter and tide gauge measurements at 30 island locations in the central and western Pacific.Documents
| USA |
Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (16 Aug 1994 - 15 Sep 1994) to (16 Jul 1995 - 15 Aug 1995) by 1.0 N= 12 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (120E) to (120W) by 6.0 N= 21 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (40S) to (40N) by 1.333333 N= 61 pts :grid
Other Info
- CE
- null
- CI
- 4.0
- CS
- null
- datatype
- realarraytype
- file_missing_value
- 999
- missing_value
- NaN
- units
- cm
- standard units*
- 0.01 meter
- history
- $partialdiff sub X$ $integral dX$ $integral dT$ $partialdiff sub T$ [ IGOSS ers1 sealevel ]
- Blended sea level anomaly from ERS-1 altimeter data and tide gauge data.
Annual and semiannual signals have been removed, leaving only the interannual changes relative to the April 1985-86 mean.
- Blended sea level anomaly from ERS-1 altimeter data and tide gauge data.
References
Miller et al. Blending ERS-1 Altimetry and Tide-Gauge Data, Eos Trans. AGU 74, 16, 1993.
Last updated: Fri, 18 Sep 2015 18:39:07 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $partialdiff sub X$ $integral dX$ $integral dT$ $partialdiff sub T$ [ IGOSS ers1 sealevel ] [ X Y | T] | 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 T
- Differentiate along X Y T
- Take differences along X Y T
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units