served from IRI/LDEO Climate Data Library
∫dY [ UEA CRU New CRU05 monthly cld ]: cloud cover data
CRU05 monthly cld 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 (Jan 1901) to (Dec 1995) by 1.0 N= 1140 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 (90S) to (90N) by 0.5 N= 361 pts :grid
Other Info
- bufferwordsize
- 8
- datatype
- doublearraytype
- file_missing_value
- -9999
- missing_value
- NaN
- units
- 0.000174532925199433 radian north
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
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $integral dY$ [ 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
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units