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MaliMeteo ENACTS ENACTS_v2 MON Rainfall dekadal precip_vs_meanprecip: Reconstructed Rainfall Expressed as Percentages of the Long-Term Average data
ENACTS ENACTS_v2 MON Rainfall dekadal Reconstructed Rainfall Expressed as Percentages of the Long-Term Average from MaliMeteo: Mali-Météo.Independent Variables (Grids)
- Time
- grid: /T (days since 1960-01-01) ordered [ (1-10 Jan 1981) (11-20 Jan 1981) (21-31 Jan 1981) ... (11-20 Jun 2023)] N= 1529 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (12.525W) to (4.5375E) by 0.0375 N= 456 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (9.8625N) to (25.35N) by 0.0375 N= 414 pts :grid
Other Info
- CE
- 300
- colorscalename
- rfepercent_colors
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -99.0
- maxncolor
- 254
- scale_max
- 300.0
- scale_min
- 0.0
- units
- unitless
- history
- Averaged over T2[0.5, 1080.5] minimum 0.0% data present
- colorscale
Last updated: Fri, 15 Sep 2023 09:17:58 GMT
Expires: Mon, 21 Aug 2023 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 | |
 MaliMeteo ENACTS ENACTS_v2 MON Rainfall dekadal precip_vs_meanprecip[ 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