served from IRI/LDEO Climate Data Library
∫dS [ ∂S S ]: ∂S forecast start time data
∫dS [ ∂S S ].Independent Variables (Grids)
- forecast start time (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered (0000 9 Nov 2015) to (0000 10 Aug 2023) by 1.0 N= 2832 pts :grid
Other Info
- bufferwordsize
- 8
- datatype
- doublearraytype
- gridid
- 198196800
- pointwidth
- 0.0
- scale_max
- null
- scale_min
- null
- standard_name
- forecast_reference_time
- units
- days
- standard units*
- 86400 second
Last updated: Fri, 01 Sep 2023 11:19:10 GMT
Data Views
Views
line plots
color bars
scatter| L | M | S | X | Y | |
 ECMWF S2S ISAC forecast perturbed sfc_precip tp[ X Y | M L S] | M | M | M | M | M |
|---|---|---|---|---|---|
| grid: /S (days since 1960-01-01) ordered (0000 9 Nov 2015) to (0000 10 Aug 2023) by 1.0 N= 2832 pts :grid | M | ||||
| grid: /S (days since 1960-01-01) ordered (0000 9 Nov 2015) to (0000 10 Aug 2023) by 1.0 N= 2832 pts :grid | M | ||||
| grid: /Y (degree_north) ordered (90N) to (90S) by 2.5 N= 73 pts :grid | M | ||||
| grid: /M (ids) ordered (1) to (40) by 1.0 N= 40 pts :grid | M | ||||
 $integral dS$ [ $partialdiff sub S$ S ][ S |] | 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 S
- Differentiate along S
- Take differences along S
RMS (root mean square with mean *not* removed) over S |
RMSA (root mean square with mean removed) over S |
Maximum over S |
Minimum over S |
Detrend (best-fit-line) over S |
Note on units