served from IRI/LDEO Climate Data Library
∫dX ∫dY [ IGOSS australia u ] : zonal surface wind data
u int_dY zonal surface wind from IGOSS australia: Surface winds from the Australian Bureau of Meteorology in Melbourne.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Aug 1995) to (Aug 2002) by 1.0 N= 85 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (178.75E) to (178.75E) by 2.5 N= 145 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (91.25S) to (91.25N) by 2.5 N= 74 pts :grid
Other Info
- bufferwordsize
- 8
- datatype
- doublearraytype
- file_missing_value
- 9999.0
396.0 - missing_value
- NaN
- units
- 0.000304617419786709 meter radian2 east second-1
- history
- The surface winds are calculated using boundary layer similarity theory. AUSTRALIA
Last updated: Mon, 16 Feb 2015 21:51:22 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $integral dX$ $integral dY$ [ IGOSS australia u ] [ X Y | T] | M | M | M |
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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