served from IRI/LDEO Climate Data Library
∂M min detrended-bfl detrended-bfl [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] : ∂M Accumulated Total Precipitation data
forecast perturbed sfc_precip tp adif adif adif min min ∂M 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
- M (realization)
- grid: /M (ids) ordered (1.5) to (39.5) by 1.0 N= 39 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (88.75N) to (88.75S) by 2.5 N= 72 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
- kg m-2 /ids
- history
- min over X[1.253497E, 0.246521W] S[0000 9 Nov 2015, 0000 14 Nov 2019]
Last updated: Fri, 06 Dec 2019 18:45:18 GMT
Data Views
Views
data as colors
data as contours| L | M | Y | |
 $partialdiff sub M$ min detrended-bfl detrended-bfl [ ECMWF S2S ISAC forecast perturbed sfc_precip tp ] [ Y L | M] | M | M | M |
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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 M
- Differentiate along Y L M
- Take differences along Y L M
RMS (root mean square with mean *not* removed) over Y L M | Y L Y M L M | Y L M |
RMSA (root mean square with mean removed) over Y L M | Y L Y M L M | Y L M |
Maximum over Y L M | Y L Y M L M | Y L M |
Minimum over Y L M | Y L Y M L M | Y L M |
Detrend (best-fit-line) over Y L M | Y L Y M L M | Y L M |
Note on units