served from IRI/LDEO Climate Data Library
min max ∂X root mean sq anom ∂L ∂Y [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] : ∂X ∂L ∂Y Accumulated Total Precipitation data
forecast perturbed sfc_precip tp partial_Y partial_L partial_L partial_X max ∂X ∂L ∂Y Accumulated Total Precipitation from ECMWF S2S ISAC: ISAC-CNR Ensemble. isIndependent Variables (Grids)
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
- 0.0379954438658766 kilogram meter-2 radian-2 north second-1
- history
- max $partialdiff sub X$ root mean sq anom $partialdiff sub L$ $partialdiff sub Y$ [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] 0000 14 Nov 2019
- Averaged over Y[88.75N, 88.75S] L[0.5 days, 30.5 days] minimum 0.0% data present
max over M[1, 40]
min max $partialdiff sub X$ root mean sq anom $partialdiff sub L$ $partialdiff sub Y$ [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ]- min over X[1.253496W, 0.246521W] S[0000 9 Nov 2015, 0000 14 Nov 2019]
- Averaged over Y[88.75N, 88.75S] L[0.5 days, 30.5 days] minimum 0.0% data present
Last updated: Fri, 06 Dec 2019 18:45:18 GMT
Data Views
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
- Differentiate along
- Take differences along
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units