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min [ IRI CPT JAS WDF History Input_WDF ]: Wet day frequency input observations data
Input_WDF Wet day frequency input observations from IRI CPT JAS WDF History: Predictand, Hindcast and Skill.Independent Variables (Grids)
- Longitude (longitude)
- grid: /X (degree_east) ordered (16.75W) to (19.75E) by 0.5 N= 74 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (5.25N) to (19.75N) by 0.5 N= 30 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- colorscalename
- precip_colors
- CS
- 0
- datatype
- doublearraytype
- file_missing_value
- -999.0
- maxncolor
- 254
- missing_value
- NaN
- scale_min
- 0.0
- units
- days
- standard units*
- 86400 second
- history
- min over S[0000 1 Apr 1982, 0000 1 Apr 2014]
Last updated: Fri, 01 Jun 2018 13:30:16 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts
line plots
color bars| X | Y | |
 min [ IRI CPT JAS WDF History Input_WDF ][ 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
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