served from IRI/LDEO Climate Data Library
∫dS root mean sq anom ∫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)
- S (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered (1200 8 Nov 2015) to (1200 14 Nov 2019) by 1.0 N= 1468 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic [ (2.506993E) (5.013986E) (7.520978E) ... (1.006958E)] N= 144 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
- 86400 kilogram meter-2 second
- history
- Averaged over Y[91.25N, 91.25S] M[1, 40] L[0.0 days, 31.0 days] minimum 0.0% data present
Last updated: Fri, 06 Dec 2019 18:45:18 GMT
Data Views
Views
data as colors
data as contours
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 X S
- Differentiate along X S
- Take differences along X S
RMS (root mean square with mean *not* removed) over X S | X S |
RMSA (root mean square with mean removed) over X S | X S |
Maximum over X S | X S |
Minimum over X S | X S |
Detrend (best-fit-line) over X S | X S |
Note on units