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∫dT [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] climatology anomalies: Estimated Precipitation data
∫dT [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] climatology Estimated Precipitation: CPC/Famine Early Warning System Dekadal Estimates.Independent Variables (Grids)
- Time
- grid: /T (months since 1960-01-01) periodic (0000 1 Dec) to (2359 20 Nov) by 0.333333 N= 36 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (20W) to (55E) by 0.1 N= 751 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (40S) to (40N) by 0.1 N= 801 pts :grid
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- maxncolor
- 254
- units
- 86.4 meter second
- history
- $integral dT$ [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] climatology
Averaged over T2[0001 26 Nov 1999 - 0001 26 Nov 2000, 2357 25 Nov 2024 - 2357 25 Nov 2025]
- $integral dT$ [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] climatology climatology
- Averaged over T2[0001 26 Nov 1999 - 0001 26 Nov 2000, 2357 25 Nov 2024 - 2357 25 Nov 2025]
Averaged over T2=26 Nov 1960 - 25 Nov 1961
- Averaged over T2[0001 26 Nov 1999 - 0001 26 Nov 2000, 2357 25 Nov 2024 - 2357 25 Nov 2025]
- $integral dT$ [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] climatology
References
Love,T 2002: The Climate Prediction Center Rainfall Algorithm Version 2
Last updated: Tue, 15 Aug 2017 14:04:01 GMT
Expires: Mon, 21 Aug 2017 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $integral dT$ [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] climatology anomalies[ 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