served from 129.236.110.25
mean ∫dX ∂Y [ Princeton wspd ] : ∂Y Wind speed at 10 m data
mean ∫dX ∂Y [ Princeton wspd ] . isIndependent Variables (Grids)
- Depth
- grid: /Z (m) ordered [ (0)] :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 2.00000004E20
- missing_value
- NaN
- pointwidth
- 0
- units
- m /s
- standard units*
- meter second-1
- history
- Averaged over X[0, 0] Y[89.75S, 89.75N] T[0000 1 Jan 1948, 2400 30 Dec 2008] minimum 0.0% data present
Last updated: Fri, 27 Nov 2020 04:20:45 GMT
Data Views
| Z | |
 Princeton[prcp
tmin
tmax
wspd
] | |
| grid: /X (degree_east) periodic (0.25E) to (0.25W) by 0.5 N= 720 pts :grid | |
| grid: /Y (degree_north) ordered (89.75S) to (89.75N) by 0.5 N= 360 pts :grid | |
| grid: /T (days since 1960-01-01 00:00:00) ordered (0000 1 Jan 1948) to (0000 31 Dec 2008) by 1.0 N= 22281 pts :grid | |
 mean $integral dX$ $partialdiff sub Y$ [ Princeton wspd ] 0 m[ Z |] | 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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units