served from 129.236.110.25
min root mean sq anom ∫dY ∂Y [ Princeton wspd ] : ∂Y Wind speed at 10 m data
min root mean sq anom ∫dY ∂Y [ Princeton wspd ] .Independent Variables (Grids)
- Time (time)
- grid: /T (days since 1960-01-01 00:00:00) ordered (1 Jan 1948) to (30 Dec 2008) by 1.0 N= 22280 pts :grid
- 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
- min root mean sq anom $integral dY$ $partialdiff sub Y$ [ Princeton wspd ]
- Averaged over Y[89.75S, 89.75N] minimum 0.0% data present
min over X[0.25E, 0.25W]
- Averaged over Y[89.75S, 89.75N] minimum 0.0% data present
Last updated: Fri, 27 Nov 2020 04:20:45 GMT
Data Views
Views
line plots
color bars
scatter| T | 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 | D | |
 min root mean sq anom $integral dY$ $partialdiff sub Y$ [ Princeton wspd ] 0 m[ Z | T] | 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 T
- Differentiate along T
- Take differences along T
RMS (root mean square with mean *not* removed) over T |
RMSA (root mean square with mean removed) over T |
Maximum over T |
Minimum over T |
Detrend (best-fit-line) over T |
Note on units