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min ∂X ∫dT ∫dY [ Estation vgt-dmp v2p0 SPOTV-ECOWAS dmp ] : ∂X Productivité en matière sèche data
dmp int_dY int_dT partial_X ∂X Productivité en matière sèche from Estation vgt-dmp v2p0 SPOTV-ECOWAS: SPOT-ECOWAS dmp.Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) ordered [ (0000 1 Jan 2019) (0000 11 Jan 2019) (0000 21 Jan 2019) (0000 1 Feb 2019) (0000 11 Feb 2019) (0000 21 Feb 2019) (0000 1 Mar 2019) (0000 11 Mar 2019) (0000 21 Mar 2019) (0000 1 Apr 2019) (0000 11 Apr 2019) (0000 21 Apr 2019) (0000 1 May 2019) (0000 11 May 2019) (0000 21 May 2019) (0000 1 Jun 2019) (0000 11 Jun 2019) (0000 21 Jun 2019) (0000 1 Jul 2019) (0000 11 Jul 2019) (0000 21 Jul 2019) (0000 1 Aug 2019) (0000 11 Aug 2019) (0000 21 Aug 2019) (0000 1 Sep 2019)] :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (28.00893N) to (3.998847N) by 0.008929 N= 2690 pts :grid
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- missing_value
- NaN
- units
- 8.64 kilogram meter-2 second
- history
- min over X[19.0W, 24.99319E]
Last updated: Sat, 12 Jun 2021 03:19:49 GMT
Data Views
Views
data as colors
data as contours| T | Y | |
 Estation vgt-dmp v2p0 SPOTV-ECOWAS[dmp
] | ||
 min $partialdiff sub X$ $integral dT$ $integral dY$ [ Estation vgt-dmp v2p0 SPOTV-ECOWAS dmp ] [ Y | T] | 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 Y T
- Differentiate along Y T
- Take differences along Y T
RMS (root mean square with mean *not* removed) over Y T | Y T |
RMSA (root mean square with mean removed) over Y T | Y T |
Maximum over Y T | Y T |
Minimum over Y T | Y T |
Detrend (best-fit-line) over Y T | Y T |
Note on units