data: min [ T , root mean sq root mean sq min $integral dT$ ( Princeton wspd ) ]

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min [ T , root mean sq root mean sq min ∫dT ( Princeton wspd ) ]: Time, Wind speed at 10 m data

min [ T , root mean sq root mean sq min ∫dT ( 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

calendar

standard

datatype

realarraytype

fnname

min

gridid

175570728

missing_value

NaN

pointwidth

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

root mean sq min $integral dT$ [ Princeton wspd ]

min over Y[89.75S, 89.75N]
Averaged over X[0, 0] minimum 0.0% data present

root mean sq root mean sq min $integral dT$ [ Princeton wspd ]

Averaged over T[1200 31 Dec 1947, 1200 31 Dec 2008] minimum 0.0% data present

Last updated: Fri, 27 Nov 2020 04:20:45 GMT

Data Views

	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
min [ T , root mean sq root mean sq min $integral dT$ ( 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