served from IRI/LDEO Climate Data Library
∂S root mean sq root mean sq [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] : ∂S Accumulated Total Precipitation data
forecast perturbed sfc_precip tp tp tp ∂S Accumulated Total Precipitation from ECMWF S2S ISAC: ISAC-CNR Ensemble.Independent Variables (Grids)
- S (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered (9 Nov 2015) to (9 Aug 2023) by 1.0 N= 2831 pts :grid
Other Info
- CE
- null
- CS
- null
- datatype
- realarraytype
- file_missing_value
- 9.99900026E20
- gribPDSpattern
- 04XXXX000B0134
- missing_value
- NaN
- pointwidth
- 0.0
- standard_name
- precipitation_amount
- units
- 1.15740740740741×10-05 kilogram meter-2 second-1
- history
- $partialdiff sub S$ root mean sq root mean sq [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ]
- Averaged over Y[91.25S, 91.25N] M[1, 40] L[0.0 days, 31.0 days] minimum 0.0% data present
Averaged over X[1.253497W, 0.2464905W] minimum 0.0% data present
- Averaged over Y[91.25S, 91.25N] M[1, 40] L[0.0 days, 31.0 days] minimum 0.0% data present
Last updated: Fri, 10 Nov 2023 19:23:03 GMT
Data Views
Views
line plots
color bars
scatter| S | |
 $partialdiff sub S$ root mean sq root mean sq [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] [ | 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