data: $partialdiff sub Y$ mean $partialdiff sub T$ [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est

served from maproom.meteorwanda.gov.rw

∂_Y mean ∂_T [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] : ∂_Y ∂_T Estimated Precipitation data

∂_Y ∂_Y ∂_T Estimated Precipitation: CPC/Famine Early Warning System Dekadal Estimates.

Independent Variables (Grids)

Longitude (longitude): grid: /X (degree_east) ordered (20W) to (55E) by 0.1 N= 751 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (39.95S) to (39.95N) by 0.1 N= 800 pts :grid

Other Info

CE: null
CS: null
datatype: realarraytype
maxncolor: 254
units: 6.63145596216231×10^-07 meter radian^-1 north second^-1
history: Averaged over T[6-15 Dec 1999, 2400 5 Jun 2026]

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

	X	Y
$partialdiff sub Y$ mean $partialdiff sub T$ [ NOAA NCEP CPC FEWS Africa TEN-DAY RFEv2 est_prcp ] [ X Y \|]	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
Differentiate along X Y
Take differences along X Y

Average over X Y | X Y |
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |

Note on units