data: $integral dX$ $partialdiff sub T$ [ UEA CRU New CRU05 monthly cld ]

served from IRI/LDEO Climate Data Library

∫dX ∂_T [ UEA CRU New CRU05 monthly cld ] : ∂_T cloud cover data

CRU05 monthly cld partial_T ∂_T cloud cover from UEA CRU New: Mean surface climate data over global land areas, including tercile and percentile data.

Independent Variables (Grids)

Time (time): grid: /T (months since 1960-01-01) ordered (16 Jan 1901 - 15 Feb 1901) to (16 Nov 1995 - 15 Dec 1995) by 1.0 N= 1139 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (180W) to (180) by 0.5 N= 721 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (89.75S) to (89.75N) by 0.5 N= 360 pts :grid

Other Info

bufferwordsize: 8
datatype: doublearraytype
file_missing_value: -9999
missing_value: NaN
units: 0.0020943951023932 radian east year^-1

References

Mark New, Mike Hulme, and Phil Jones, Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology,Journal of Climate: Vol. 12, No. 3, pp. 829–856.

Last updated: Mon, 12 Sep 2016 21:33:44 GMT

Data Views

	T	X	Y
$integral dX$ $partialdiff sub T$ [ UEA CRU New CRU05 monthly cld ] [ X Y \| T]	M	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 X Y T
Differentiate along X Y T
Take differences along X Y T