max mean ∫dY ∂X detrended-bfl [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] : ∂X Accumulated Total Precipitation data
forecast perturbed sfc_precip tp adif adif partial_X int_dY int_dY
∂X Accumulated Total Precipitation from ECMWF S2S ISAC: ISAC-CNR Ensemble.
Independent Variables (Grids)
- Lead (forecast_period)
- grid: /L (days) ordered (0.0 days) to (31.0 days) by 1.0 N= 32 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (91.25N) to (91.25S) by 2.5 N= 74 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- 9.99900026E20
- gribPDSpattern
- 04XXXX000B0134
- missing_value
- NaN
- pointwidth
- 0.0
- standard_name
- precipitation_amount
- units
- kg m-2
- standard units*
- kilogram meter-2
- history
- max mean $integral dY$ $partialdiff sub X$ detrended-bfl [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ]
- Averaged over S[0000 9 Nov 2015, 2400 6 Nov 2019] minimum 0.0% data present
max over X[2.506993E, 1.006958E] M[1, 40]
Last updated: Fri, 29 Nov 2019 18:05:42 GMT
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 Y
L
- Differentiate along Y
L
- Take differences along Y
L
Average over
Y
L
|
Y L
|
RMS (root mean square with mean *not* removed) over
Y
L
|
Y L
|
RMSA (root mean square with mean removed) over
Y
L
|
Y L
|
Maximum over
Y
L
|
Y L
|
Minimum over
Y
L
|
Y L
|
Detrend (best-fit-line) over
Y
L
|
Y L
|
Note on units