data: $partialdiff sub Y$ $integral dT$ [ UEA CRU New CRU05 monthly wet ]

served from IRI/LDEO Climate Data Library

∂_Y ∫dT [ UEA CRU New CRU05 monthly wet ] : ∂_Y wet day frequency data

CRU05 monthly wet int_dT ∂_Y wet day frequency 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 (0000 1 Jan 1901) to (0000 1 Jan 1997) by 1.0 N= 1153 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (179.75W) to (179.75E) by 0.5 N= 720 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (89.5S) to (89.5N) by 0.5 N= 359 pts :grid

Other Info

CE: null
CS: null
datatype: realarraytype
file_missing_value: -999.90002
missing_value: NaN
units: 4950355.34993031 radian^-1 north second

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: Wed, 13 Feb 2019 20:27:28 GMT

Data Views

	T	X	Y
$partialdiff sub Y$ $integral dT$ [ UEA CRU New CRU05 monthly wet ] [ 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