served from 129.236.110.25
mean min [ T , min ∂T ( Princeton wspd ) ] : Time, ∂T Wind speed at 10 m data
mean min [ T , min ∂T ( Princeton wspd ) ] .Independent Variables (Grids)
- Time (time)
- grid: /T (julian_day) ordered (0000 1 Jan 1948) to (0000 31 Dec 2008) by 1.0 N= 22281 pts :grid
Other Info
- bufferwordsize
- 8
- calendar
- standard
- CE
- null
- CS
- null
- datatype
- doublearraytype
- fnname
- min
- gridid
- 175570704
- missing_value
- NaN
- pointwidth
- 0
- scale_max
- null
- scale_min
- null
- standard_name
- time
- units
- days since 1960-01-01 00:00
- standard units*
- 86400 ( seconds since 1960-01-01 00:00.000 )
- history
- mean min [ T , min $partialdiff sub T$ ( Princeton wspd ) ]
- min over X[0.25E, 0.25W] T[1200 1 Jan 1948 - 1200 2 Jan 1948, 1200 29 Dec 2008 - 1200 30 Dec 2008]
Averaged over Y[90S, 90N] minimum 0.0% data present
- min over X[0.25E, 0.25W] T[1200 1 Jan 1948 - 1200 2 Jan 1948, 1200 29 Dec 2008 - 1200 30 Dec 2008]
Last updated: Fri, 27 Nov 2020 04:20:45 GMT
Data Views
Views
line plots
color bars
scatter| T | |
 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 | |
 mean min [ T , min $partialdiff sub T$ ( Princeton wspd ) ] [ T |] | 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