served from IRI/LDEO Climate Data Library
UEA CRU Global prcp: Precipitation data
Precipitation from UEA CRU Global: Historical monthly precipitation dataset for global land areas.Independent Variables (Grids)
- Time
- grid: /T (months since 1960-01-01) ordered (Jan 1900) to (Dec 1996) by 1.0 N= 1164 pts :grid
- longitude
- grid: /X (degree_east) periodic (180W) to (176.25E) by 3.75 N= 96 pts :grid
- latitude
- grid: /Y (degree_north) ordered (87.5S) to (87.5N) by 2.5 N= 71 pts :grid
Other Info
- datatype
- realarraytype
- missing_value
- -999.0
- units
- mm /month
- standard units*
- 0.012 meter year-1
- history
- CRU Gridded Global Precip Dataset 3.75x2.5
References
Hulme,M. (1992) A 1951-80 global land precipitation climatology for the evaluation of General Circulation Models Climate Dynamics, 7, 57-72Hulme,M. (1994) Validation of large-scale precipitation fields in General Circulation Models pp.387-406 in, Global precipitations and climate change (eds.) Desbois,M. and Desalmand,F., NATO ASI Series, Springer-Verlag, Berlin, 466pp.
Last updated: Mon, 12 Sep 2016 21:11:40 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 UEA CRU Global prcp[ X Y | T] | M | M | M |
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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