served from 181.199.253.14
∫dY ∫dSh ∂X [ Hydromet Seasonal_Forecast Precipitation History InputObs ] : ∂X input observations data
InputObs partial_X int_dSh ∂X 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
- Sh
- grid: /Sh (months since 1960-01-01) ordered (0000 16 Dec 1980) to (0000 16 Dec 2010) by 1.0 N= 361 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (61.5W) to (56.5W) by 0.05 N= 101 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (1N) to (8.549999N) by 0.04999999 N= 152 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
- 8.33333333333333×10-05 meter year
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 | Sh | X | Y | |
 $integral dY$ $integral dSh$ $partialdiff sub X$ [ Hydromet Seasonal_Forecast Precipitation History InputObs ] 2.5 months[ Sh | X Y L] | M | 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 Sh X Y
- Differentiate along Sh X Y
- Take differences along Sh X Y
RMS (root mean square with mean *not* removed) over Sh X Y | Sh X Sh Y X Y | Sh X Y |
RMSA (root mean square with mean removed) over Sh X Y | Sh X Sh Y X Y | Sh X Y |
Maximum over Sh X Y | Sh X Sh Y X Y | Sh X Y |
Minimum over Sh X Y | Sh X Sh Y X Y | Sh X Y |
Detrend (best-fit-line) over Sh X Y | Sh X Sh Y X Y | Sh X Y |
Note on units