served from 181.199.253.14
max ∂Y ∫dSh [ Hydromet Seasonal_Forecast Precipitation History InputObs ] : ∂Y input observations data
InputObs int_dSh partial_Y ∂Y input observations from Hydromet Seasonal_Forecast Precipitation History: Predictand and Hindcast.Independent Variables (Grids)
- Forecast Lead Time in Months
- grid: /L (months) ordered [ (2.5)] :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (61.525W) to (56.475W) by 0.05000003 N= 102 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (1.05N) to (8.5N) by 0.05 N= 150 pts :grid
Other Info
- CE
- 1700
- CS
- 0
- datatype
- realarraytype
- file_missing_value
- -9999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- 0.00477464829275686 meter radian-1 north year
- history
- max over Sh[0000 16 Dec 1980, 0000 16 Dec 2010]
- colorscale
Last updated: Fri, 12 Jan 2024 14:16:35 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | X | Y | |
 max $partialdiff sub Y$ $integral dSh$ [ Hydromet Seasonal_Forecast Precipitation History InputObs ] 2.5 months[ | X Y L] | 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
- 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