served from 181.199.253.14
root mean sq ∂Sh [ Hydromet Seasonal_Forecast Precipitation History InputObs ] : ∂Sh input observations data
InputObs partial_Sh ∂Sh 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 (1.025N) to (8.525N) by 0.05 N= 151 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999.0
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- units
- mm /month
- standard units*
- 0.012 meter year-1
- history
- Averaged over Sh[Jan 1981, Nov 2010] minimum 0.0% data present
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 | |
 root mean sq $partialdiff sub Sh$ [ 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